All APIs
$1.00per 1k jobs30datapoints
LinkedIn Jobs API
Extract LinkedIn job postings — title, company, location, description, salary, and full company profile — by searching with job titles, location, and filters
Sample
Sample data
Here's a sample run of job postings across roles — engineering, legal, sales, healthcare — showing the exact schema and results you can expect, including salary, recruiter, and benefits where listed.
| # | Job URL | Job Title | Description | Employment Type | Workplace Type | Remote Allowed | Experience Level | Applicants | Posted | Expires | Apply URL | Easy Apply | Industries | Salary Min | Salary Max | Salary Currency | Salary Period | ATS | Benefits | Recruiter Name | Recruiter URL | City | State | Country | Company Name | Company URL | Company Logo | Company Website | Company Employees | Company Followers |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | AI Engineer | We are seeking a Senior AI Engineer with deep, hands on expertise in Generative AI, multi agent orchestration, and LLM based systems with Python to design, build, and scale secure, production grade AI platforms. The role requires strong engineering rigor, practical experience beyond PoCs, and the ability to operationalize agentic AI in complex enterprise environments.________________________________________
Roles & ResponsibilitiesCore Skills & ResponsibilitiesGenerative AI & LLM Engineering• Strong hands on experience building LLM powered applications for reasoning, summarization, Q&A, and content generation• Expertise in prompt engineering, prompt optimization, and systematic prompt evaluation• Ability to generate structured and deterministic outputs for downstream consumption• Apply grounding, response validation, and hallucination mitigation techniques________________________________________Multi Agent Orchestration & LangGraph (Must Have)• Strong hands on experience designing and implementing multi agent AI systems• Practical experience working with agent orchestration frameworks, specifically LangGraph• Design and implement:o Orchestrator / supervisor agent patternso Intent routing, task decomposition, and agent sequencingo Dependency management and agent handoffs• Implement tool calling patterns, shared context management, and output aggregation across agents• Experience managing agent state, memory, and execution flow in production environments________________________________________Retrieval Augmented Generation (RAG)• Build and optimize RAG pipelines across large unstructured datasets• Hands on experience with:o Embedding strategieso Vector databases and semantic searcho Chunking, ranking, and metadata based retrieval• Ensure responses are traceable, explainable, and source grounded________________________________________AI Application Engineering• Strong backend engineering skills using Python• Design modular, API first AI services using scalable architectures• Integrate AI services with external systems and tools via secure APIs• Efficient handling of long running agent workflows and asynchronous execution________________________________________Cloud Native AI & Platform Skills• Experience deploying AI solutions on cloud native platforms• Familiarity with:o Containerized AI workloadso CI/CD pipelines for AI and agent serviceso Scalable, fault tolerant system design• Experience managing structured and unstructured data storage for AI workloads________________________________________AI Governance, Security & Reliability• Implement guardrails and safety controls, including:o Prompt injection preventiono Access control and role based executiono Output validation and policy enforcement• Support observability for:o Agent behavior and execution flowo Confidence scoring and failure detectiono Usage patterns and anomaly detection• Design AI systems that are auditable, explainable, and enterprise ready________________________________________Collaboration & Technical Leadership• Provide technical leadership across AI and GenAI initiatives• Review AI designs, orchestration flows, and implementation quality• Mentor junior AI engineers on agent design and best practices• Collaborate with architects, data scientists, and platform engineers________________________________________Required Qualifications• Strong experience as a Senior AI / GenAI Engineer• Proven, hands on experience with multi agent orchestration using LangGraph• Advanced knowledge of:o LLMs and agentic AI systemso RAG architectureso Python based AI development• Experience delivering production grade AI systems, not just experiments________________________________________Preferred Qualifications• Experience designing large scale agent based platforms• Exposure to LLMOps / MLOps practices• Familiarity with model and agent evaluation techniques• Experience working in regulated or security sensitive environments________________________________________Key Expectations• Deliver scalable, reliable, and well orchestrated AI systems• Demonstrate deep hands on ownership of multi agent execution logic• Balance innovation with robustness, security, and maintainability | contract | on_site | false | Mid-Senior level | 27 | 2026-06-24T23:36:23.000Z | 2026-07-24T23:36:22.000Z | true | 60 | 63 | USD | HOURLY | LinkedIn | — | Himanshu Aneja | San Francisco | California | United States | NAM Info Inc | 190 | 125,581 | |||||||
2 | Machine Learning Engineer | About GitHub
GitHub is the world’s leading platform for agentic software development — powered by Copilot to build, scale, and deliver secure software. Over 180 million developers, including more than 90% of the Fortune 100 companies, use GitHub to collaborate, and more than 77,000 organisations have adopted GitHub Copilot.
Locations
In this role you can work from Remote, United States
Overview
GitHub is changing the way the world builds software and we want you to help build and secure GitHub. We're looking for an experienced machine learning engineer to help design, build and deploy agentic solutions, and to conduct ad-hoc analysis, as you help protect the home of all developers.
You will be responsible for identifying new trends relating to safety, fraud and abuse on GitHub, building agentic solutions to detect this abuse at scale, identifying vulnerabilities in GitHub that lead to abuse and helping to measure the impact of our work to safeguard the platform. At GitHub, Safety and Integrity's mission is to ensure GitHub and our users' safety through fighting malware, spam and fraud, monitoring for fake accounts, countering inauthentic content, battling crypto mining, and other core areas. You will be involved in collaborations across teams within GitHub including with Copilot and setting the standard for effective and responsible use of AI for moderation and trust and safety purposes, ensuring fraud is countered, content is moderated, users are kept safe and the open-source community can flourish.
If you have a strong foundation in large language models, solid software engineering instincts, a working knowledge of online platform trust and safety issues, and an empathetic approach to collaborating with a diverse team from entry-level associates to seasoned senior contributors, then this might be the gig for you.
What We Value
Collaboration: We believe the best work is done together. Empathy: We believe in putting people first. Quality: We believe in setting the standard for excellence. Positive Impact: We believe in making the world a better place through our work. Shipping: We believe in creating things for the people using them.
Responsibilities
Design, build and deploy agentic solutions that leverage large language models to detect and prevent fraud, abuse, and security threats at scale — applying LLMs to problems such as content classification and multi-step agentic investigation. Build well-engineered, production-grade systems that run reliably against high-volume event streams, making effective use of AI coding assistants to accelerate and improve your work. Build and operate scalable ML systems on cloud platforms (such as Azure AI Foundry) for training, deploying, and serving models and agentic solutions in production. Evaluate and improve existing models and agentic solutions using offline evaluations (including tool-use loops and LLM-as-judge evaluation), performance metrics, and feedback from operational deployments. Identify vulnerabilities in products that lead to abuse, and provide consultation to product teams reviewing new features. Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate agentic solutions into production systems. Document the systems you help build and support the technical growth of your peers.
Qualifications
Required Qualifications
4+ years experience in machine learning, or related fieldOR Bachelor's Degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 2+ years experience in machine learning, or related field OR Master's Degree in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field OR equivalent experience.
Preferred Qualifications
Strong understanding of large language models — how they work — and hands-on experience applying them at scale, ideally for classification, agentic workflows, or agents. Strong software engineering skills, including experience building with AI coding assistants. Experience designing or evaluating agentic systems (tool-use loops, multi-step workflows, or LLM-as-judge evaluation). Hands-on experience building and operating classification or detection systems at scale, including handling imbalanced data and precision/recall tradeoffs. Experience in Trust and Safety, National Security or fighting spam, malware, fraud, and threat actor activity at scale. Experience in responsible AI. Experience in Safety-by-Design. Experience with managing user data and privacy. Solid understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and their practical implementation.
Compensation Range
The base salary range for this job is USD $107,700.00 - USD $285,900.00 /Yr.
These pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. At GitHub certain roles are eligible for benefits and additional rewards, including annual bonus and stock. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee's role.
This position will be open for a minimum of 3 days, with applications accepted on an ongoing basis until the position is filled.
GitHub values
Customer-obsessedShip to learnGrowth mindsetOwn the outcomeBetter togetherDiverse and inclusive
Manager fundamentals
ModelCoachCare
Leadership principles
Create clarityGenerate energyDeliver success
Who We Are
GitHub is the world’s leading AI-powered developer platform with 150 million developers and counting. We’re also home to the biggest open-source community on earth (and 99% of the world’s software has open-source code in its DNA). Many of the apps and programs you use every day are built on GitHub.
Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We’re remote-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are—because we know that people flourish when they can work on their own terms.
Join us, and let’s change the world, together.
EEO Statement
GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate! | full_time | remote | true | — | 25 | 2026-06-25T06:00:02.000Z | 2026-07-25T06:00:02.000Z | false | — | — | — | — | — | — | — | — | — | — | United States | GitHub | 6,478 | 6,283,737 | ||||||
3 | Senior Machine Learning Engineer, MLOps West Coast | Job Requisition ID #
26WD96432
Position Overview
The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world.
As a Senior Machine Learning Engineer focused on Machine Learning Ops (MLOps) for CAD and BIM, you will ensure AI-powered experiences meet high standards for reliability, scalability, and operational excellence across Autodesk products. You will build and operate the infrastructure that takes models from development into production, including deployment automation, monitoring, and secure, scalable service integration. You will partner closely with researchers, evaluation engineers, and product teams to translate evaluation requirements into production quality gates, reduce operational risk, and continuously improve model performance in real customer environments.
You will report to a manager in the Model Delivery team within Autodesk Research. This role is based in proximity to our North American west coast offices, including San Francisco, Portland, and Vancouver. We support both in-person, hybrid, and remote work.
Responsibilities
Test and Deploy Production Models: Automate model testing and validation. Implement and operate CI/CD pipelines to enable safe, repeatable deployments and rollbacks.Operate Inference Services: Provision and manage backend resources for inference (compute, containers, scaling), and tune performance, reliability, and cost in production.Monitor Model Health and Performance: Define and continuously monitor health and performance metrics for deployed services. Triage issues by severity and drive timely resolution, including incident response and runbooks.REST API Integration: Own end-to-end REST API integration, connecting backend model services to product and platform surfaces through scalable, containerized services.Product Ownership and Cross-functional Collaboration: Work with researchers, evaluation engineers, product managers, and partner engineering teams to deliver production-ready solutions, communicate status and risks, and escalate when needed.
Minimum Qualifications
BS or MS in Computer Science, Computer Engineering, or equivalent industry experience.3+ years of professional software engineering experience building and operating production services.Experience automating testing and deployments using CI/CD, including release workflows that support safe rollouts and rollbacks.Experience building and operating cloud hosted, containerized services (for example Docker and Kubernetes or similar), including provisioning resources and scaling inference workloads.Experience building REST APIs using Python based frameworks (or similar), and integrating backend services with product or platform consumers.Strong software engineering fundamentals: version control, code quality, and writing maintainable, testable software.Strong written communication skills to document architectures, runbooks, and operational processes.
Preferred Qualifications
Experience running production ML or LLM inference services, including performance tuning, cost optimization, and capacity planning.Experience with observability tooling and practices (metrics, logging, tracing, alerting) and incident response in an on-call environment.Experience deploying services within an enterprise internal platform environment with standardized pipelines, security controls, and compliance requirements.Familiarity with rate limiting, authentication and authorization, and API security best practices.Familiarity with design, manufacturing, or AEC workflows, and how backend services integrate into CAD/BIM product experiences.Familiarity with Agile or Scrum ways of working.
Learn More
About Autodesk
Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.
We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.
When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!
Salary transparency
Salary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $131,400 and $235,950. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $123,000 and $180,400. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
Equal Employment Opportunity
At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.
Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging
Are you an existing contractor or consultant with Autodesk?
Please search for open jobs and apply internally (not on this external site). | full_time | remote | true | Mid-Senior level | 25 | 2026-06-25T03:45:49.000Z | 2026-07-25T03:45:49.000Z | false | — | — | — | — | Workday | — | — | — | — | — | United States | Autodesk | 15,376 | 1,090,663 | ||||||
4 | Senior Mobile Software Engineer - Android | Welcome to Fi.
We’re a passionate team from Square, Google, Oura, Peloton, Uber, and more working to transform the human-pet relationship. Our mission? Develop cutting-edge technology to revolutionize what it means to be a pet parent. The pet industry remains firmly stuck in the past and we are here to change that. Fi is leveraging our team's talent and expertise to improve the lives of millions of pets in the U.S. Real-time location tracking, activity, sleep and behavior monitoring - and that's just the beginning.
The most exciting aspect of our work? Bridging the communication gap between pets and humans. Imagine a world where everyone knows how their pet feels in real time and how to keep their best friend in good shape. That's the future we're building at Fi.
If you're someone who thrives in innovative, collaborative work environments and feels strongly about helping pets live longer, better lives, Fi could be the perfect fit. Join us in our pursuit of the “impossible,” or as we call it here “let me find a way,” to redefine the future of pet ownership together.
Fi is searching for a Senior Mobile Software Engineer - Android!
Fi is looking for a Senior Mobile Software Engineer - Android to design and build dynamic, cutting-edge product experiences that redefine the pet-tech industry. This role is a unique opportunity to work with a talented, lean team, contributing directly to the development of innovative consumer-facing applications from the ground up.
If you’re excited to transform ideas into reality, develop complex interfaces, and work on a renowned consumer product, this role is for you.
What You'll Do:
Collaborate with the Director of Mobile and the engineering team to design, build, and refine innovative Android applicationsDevelop complex and dynamic user interfaces using Kotlin and Jetpack Compose (or Android Views where appropriate), ensuring seamless functionality and an exceptional user experienceContribute to the full software development lifecycle, from design and implementation to production and maintenancePlay a key role in shaping Fi’s Android development strategy and best practicesEnsure performance, quality, and responsiveness of applications through code reviews, testing, and performance tuning
What You'll Bring:
6+ years of experience as a mobile engineer, with a strong focus on Android developmentExpertise in Kotlin and a deep understanding of Android SDKs, architecture components, and modern Android development practicesExperience building and maintaining successful consumer-facing mobile apps at scaleFamiliarity with Android UI design principles, patterns, and best practicesStrong problem-solving skills and a passion for creating intuitive, performant mobile experiencesExperience with BLE, location services, or IoT integrations is a plus
Why You'll Love Us:
Time to Recharge: Enjoy flexible PTO to take the breaks you needTop-Notch Health Coverage: We’ve got your back (and teeth and eyes) with full medical, dental, and vision insuranceWellness Perks: Free access to One Medical, Kindbody, and Talkspace to keep you feeling your bestDog-Friendly Office: Bring your pup to work — they’re part of the team, tooGive Back to the Pups: Make tails wag with a $500 annual donation to a dog charity of your choice through our BarkBack ProgramFree Fi Membership: Your furry best friend(s) get all the benefits of a Fi collar, on us!Love for Friends + Family: Share the Fi magic with loved ones through our gifting program
Fi is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. This policy applies to all employment practices within our organization, including hiring, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Fi makes hiring decisions based solely on qualifications, merit, and our needs at the time.
The anticipated base salary range for this position is $150,000-$190,000. Actual compensation will vary based on multiple factors, including skills, experience, market conditions, and role scope, which may evolve during the hiring process. As a fast-growing Series B startup, Fi evaluates compensation opportunistically to align with the right candidate. This role is also eligible for equity compensation. | full_time | remote | true | — | 50 | 2026-06-24T23:39:14.000Z | 2026-07-24T23:39:13.000Z | false | 150,000 | 190,000 | USD | YEARLY | Lever | — | — | — | — | — | United States | Fi | 562 | 10,337 | ||||||
5 | Software Engineer, AI Capture | Who We Are
Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion.
Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work.
About The Role
Build the most advanced AI Meeting Notes product — and expand it into broader “AI data capture” features that help teams turn conversations into durable context, tasks, and knowledge.
Our mission is to 10x the rate of business context & data that enters Notion — optimized for agents — so teams get superhuman memory across workstreams and customers. Notion workspaces that use AI Meeting Notes already enter 6x more data on a daily basis, so we’re well on our way.
What You'll Achieve
Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership).Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization).Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable.Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems.Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “we talk and things get done.”Deliver enterprise readiness: sharing/permissions, compliance, and scalability for our fastest-growing customers.
Skills You'll Need to Bring
10+ years shipping production software, with a strong track record of owning features end-to-endStrong full-stack engineering skills (frontend + backend) and excitement to own user-facing product end-to-end.Product-minded craftsmanship: you sweat details, iterate quickly, and use data and user feedback to guide decisions.Experience building and operating production systems (debugging, on-call/incident response, performance, and reliability).Ability to work across ambiguous problem spaces, align stakeholders, and drive execution with high ownership.You don’t need to be an AI expert, but you’re curious and willing to adopt AI tools to work smarter and deliver better results.
Nice to Haves
Experience with LLM / applied AI product development (prompting, evals, model integrations, or quality measurement).Experience with media / realtime pipelines (audio, transcription, diarization, streaming, low-latency processing).Experience building for enterprise customers (permissions models, compliance, scale, and security).
Notion is committed to providing highly competitive cash compensation, equity, and benefits. The compensation offered for this role will be based on multiple factors such as location, the role’s scope and complexity, and the candidate’s experience and expertise, and may vary from the range provided below. For roles based in San Francisco, the estimated base salary range for this role is $272,000 - $320,000 per year.
By clicking “Submit Application”, I understand and agree that Notion and its affiliates and subsidiaries will collect and process my information in accordance with Notion’s Global Recruiting Privacy Policy.
A Note on AI
You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on.
Equal Opportunity & Accommodations
We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know.
Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.
| full_time | on_site | false | — | 25 | 2026-06-25T04:43:37.000Z | 2026-07-25T04:43:36.000Z | false | — | — | — | — | — | — | — | — | San Francisco | California | United States | Vizlab Ventures | 1 | 9 | ||||||
6 | AI Systems Engineer | Role: Talent Acquisition ManagerLocation: Remote (Work from Anywhere)Payout: $80–120 per hour
Role Overview:We are hiring for one of our clients, seeking a People ops / recruiting Evaluator to work on a contractual basis. This role involves reviewing AI-generated work products—such as documents, spreadsheets, and slide decks—used in people operations and recruiting functions. The work requires evaluating accuracy, rigor, and domain-specific quality to ensure outputs meet professional standards.
Key Responsibilities:• Evaluate AI-generated artifacts against domain-specific quality rubrics to assess accuracy and relevance.• Identify factual errors, inconsistencies, and aesthetic flaws in documents, spreadsheets, and slide presentations.• Grade outputs for rigor, clarity, and alignment with industry best practices in people operations and recruiting.• Provide structured, written feedback that clearly articulates strengths and areas for improvement.• Work remotely with flexibility to deliver timely, high-quality evaluations on a project basis.
Required Skills & Qualifications:• Minimum of five years of professional experience in people operations, recruiting, or related human resources functions.• Native or professional fluency in English with strong written communication skills.• High proficiency in Microsoft Office and Google Workspace, with specific expertise in Google Slides and PowerPoint.• Ability to assess technical and non-technical content with attention to detail and domain-specific standards.• Experience working with evaluation frameworks or rubrics in professional or academic settings.
More About the Opportunity:This role offers a unique opportunity to contribute to the development of AI-driven tools used in human resources and recruiting workflows at a global technology leader. Evaluators play a direct role in improving the reliability and effectiveness of AI outputs that support hiring decisions and workforce planning. The engagement is project-based and remote, allowing for schedule flexibility.
Equal Opportunity Employer:We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
Apply Now! | contract | remote | true | — | 25 | 2026-06-25T03:58:11.000Z | 2026-07-25T03:58:11.000Z | false | — | — | — | — | — | — | — | — | — | — | United States | Hire Feed | 42 | 625,911 | ||||||
7 | Forward Deployed Analytics Engineer & AI Specialist | At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
About The Role
Forward Deployed Analytics Engineers combine domain expertise with full-stack data and analytics engineering capabilities, a rare pairing that makes us Snowflake's most effective technical presence in the field. You embed directly with customer data, analytics, and business teams to build the data foundations that power Snowflake's AI platform.
This role is focused on the layers that make AI reliable: clean, well-modeled data, governed pipelines, and semantic models that expose business meaning to natural language interfaces. You will design rigorous data models, build and instrument pipelines, and construct the semantic layer that sits between raw data and AI agents. When you leave a customer engagement, their data is structured, trusted, and agent-ready. The deployment patterns and product gaps you surface feed directly back to Cortex product and research teams, making you both a practitioner and a source of signal for what gets built next.
What You'll Work On Data Modeling and Architecture
Architect flexible, performant data models that drive customers toward single sources of truth across their key business domainsUse SQL, Python, dbt, and Snowflake to build and maintain data infrastructure for reporting, analysis, and automationPerform data QA and develop automated testing procedures for Snowflake data modelsProvide input into data governance strategies including permissions, data lineage, and data definitions
Semantic Layer and Agent Readiness
Build semantic data models that expose customer tables to natural language queries via Cortex Analyst, turning complex schemas into something a business stakeholder can ask a question ofDefine and validate the metrics, dimensions, and relationships that AI agents need to reason correctly over customer dataIdentify and resolve gaps in data structure, naming, and coverage that would cause an agent to fail or produce incorrect results
Enablement and Knowledge Transfer
Build the artifacts customers leave with: documented playbooks, reusable data model templates, and semantic model libraries their teams can maintain and extendRun technical workshops to upskill customer data and analytics teams on Snowflake's AI development environmentAuthor semantic view configurations and skill files (YAML + Markdown) that a non-technical analyst can invoke in plain English
Hard Skills Required Must-Have
Advanced SQL: CTEs, window functions, incremental pipeline patterns. You can write complex queries without referencing documentation.Analytics engineering and data modeling: Experience building data infrastructure involving large-scale relational datasets; strong instincts for pipeline design, QA, and testing across the full stack from ingestion through semantic layer.Python: Modern, type-hinted, readable. You understand Python-based data pipelines and automation workflows.AI-assisted development: You have used an LLM coding assistant (CoCo, Cursor, GitHub Copilot, Claude, or equivalent) as your primary development environment. Daily usage is the baseline.Semantic modeling: You can write a semantic view configuration or structured skill file that handles edge cases and encodes enough domain knowledge that the model behaves like a subject matter expert.Client-facing communication: You write code, but your output needs to make sense to a business leader who has never opened a terminal. You are the translation layer between what Snowflake's AI can do and what the customer actually needs.
Strong Plus
dbt: Experience building and maintaining dbt projects with testing, documentation, and CI/CD pipelines.Snowflake Cortex: Cortex Analyst, Cortex Agents, Cortex Search, semantic views, Dynamic Tables.Experience with Airflow or other orchestration frameworks.Familiarity with enterprise business systems (ERP, CRM, HRIS, or similar).
Soft Skills Required
Owns the outcome: Tracks adoption after go-live, identifies stall points, and re-engages until the customer's data is reliable and their team can maintain it independently.Codifies, doesn't customize: Instinct is to turn patterns into reusable templates and playbooks that the next engineer can deploy at the next customer, not to build bespoke every time.Comfortable with ambiguity: Engages with customers to derive requirements, prototypes fast, gathers feedback, and iterates.Signal clarity: Distills messy customer deployments into clean, actionable feedback for Snowflake's product and research teams, explaining root causes and suggesting fixes, not just reporting problems.
Minimum Requirements
5+ years of experience in analytics engineering, data engineering, or a related technical role, with at least a portion of it customer-facing or cross-functionalDaily use of an AI coding assistant as a primary development toolProficient in SQL; can write window functions and complex joins without referencing documentationExperience with dbt or equivalent data modeling frameworkHas shipped at least one production data model or pipeline that non-technical business users actually relied onComfortable in Git (PRs, branches, code review)Demonstrable experience translating business requirements into technical specifications
What Success Looks Like at 90 Days
Engaged in at least two customer engagements, with measurable data quality or semantic layer improvements to show for itBuilt at least one semantic model that a customer's non-technical users can query in plain English via Cortex AnalystIdentified and resolved at least one upstream data quality or modeling issue that was blocking an AI use caseFiled at least three product feedback items that the Cortex product team has engaged with
Why This Role Is Different
Most analytics engineering roles stop at the data model. Most field roles stop at the recommendation. This role starts where both leave off. You own the full data stack from source ingestion to semantic layer, and you ensure every layer is clean, tested, and structured for AI agents to reason over reliably. You go onsite. You write the code. You build the semantic foundation. You stay until it runs in production and the customer team can maintain it.
If you are fluent in analytics engineering and Snowflake's AI development environment, you can operate at a level of customer impact that most field or internal analytics roles don't reach. Your work makes customers' data agent-ready, and your field observations make Snowflake's AI platform better.
Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
The following represents the expected range of compensation for this role:
The estimated base salary range for this role is $156,000 - $204,700.Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.
The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form. | full_time | — | false | — | 28 | 2026-06-24T23:56:44.000Z | 2026-07-24T23:56:44.000Z | false | — | — | — | — | — | — | — | — | Menlo Park | California | United States | Snowflake | 11,740 | 1,330,495 | ||||||
8 | Junior AI Engineer Entry-Level and Freshers Welcome | Job Description
Job Title
AI Engineer (Fresh Graduate)
Location
Santa Clara, CA
Remote (Remote/Hybrid based on project requirements)
Job Description
We are looking for motivated fresh graduates who are passionate about Artificial Intelligence, automation, and software development. This is a great opportunity for candidates who want to build practical skills in AI-assisted coding, workflow automation, and cloud deployment.
What You Will Learn
Using Claude by Anthropic and other AI tools to write, debug, and improve codeScripting with Python, Bash, and related technologiesWorking with Docker containersDeploying applications to cloud and Linux serversHands-on Unix / Linux system administrationBuilding workflow automations using n8nIntegrating APIs and automating business processes
Preferred Educational Background
Candidates with degrees in any of the following are encouraged to apply:
Computer ScienceInformation TechnologyElectronics and CommunicationData ScienceArtificial IntelligenceEngineering or related technical fields
Basic Requirements
Strong interest in AI, automation, and software developmentFamiliarity with programming or scripting conceptsBasic understanding of Linux/Unix commandsGood problem-solving skillsWillingness to learn new technologies quicklyStrong communication skills
Nice to Have
Exposure to Python, Shell scripting, or JavaScriptBasic knowledge of Docker and cloud deploymentInterest in AI coding tools such as Claude or OpenAIExperience with automation tools like n8n or similar platforms
Who Should Apply
Freshers, recent graduates, and candidates with internship or academic project experience who are eager to build a career in AI engineering and automation.
How to Apply
Send Your Resume Along With a Brief Note Explaining:
Why you are interested in AI and automationAny academic projects or internships you have completedTechnologies you are excited to learn
This role offers excellent hands-on learning and mentorship to help you become a skilled AI Engineer. | — | — | false | — | 34 | 2026-06-24T23:09:24.000Z | 2026-07-24T23:09:24.000Z | false | — | — | — | — | — | — | — | — | Santa Clara | California | United States | ChatGPT Jobs | 20 | 5,445 | ||||||
9 | AI Algorithm Engineer / Researcher | we are a technology company specializing in AI for Science and applying AI technologies to cutting-edge research and real-world applications in biopharmaceuticals, new materials, finance, and other fields.
Directions You Will Be Involved In
Pre-training and alignment of scientific research large models; multimodal modeling of molecules, proteins, crystals, financial time series, and more; distributed training and inference deployment; multi-agent systems (Agentic AI) for scientific discovery and quantitative strategies; frontier research and paper publication.
Systematic pre-employment training will be provided upon joining; mastery of all areas is not required beforehand.
Basic Requirements
Fresh graduates with a bachelor's or master's degree in science or engineering (Class of 2026, including overseas returnees); no restriction on major; genuine interest in AI, deep learning, and interdisciplinary applications. Proficiency in Python, familiarity with basic machine learning concepts, and ability to read English literature.
Bonus Qualifications
Experience with PyTorch projects; exposure to Transformer / LLM; participation in AI-related competitions or open-source projects; interdisciplinary background in biology, chemistry, materials science, physics, or financial engineering.
Work Location
remote from anywhere in the world | full_time | hybrid | false | — | 200 | 2026-06-24T23:29:01.000Z | 2026-12-21T23:29:01.000Z | true | — | — | — | — | — | LinkedIn | — | — | — | San Francisco | California | United States | Ainnocence | 12 | 2,131 | |||||
10 | AI Engineer, Agentic Ad Creative (Multimodal) | About NewsBreak
Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.
Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.
Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.
If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about
About The Role
Every install we buy starts as a creative someone (or something) made. We're rebuilding that creative pipeline so that *something* is an agent — one that generates thousands of images and videos a day across Meta, Google, TikTok, Pinterest, Reddit, and Snap; watches CPI and ROAS come back; and gets sharper every cycle.
We're hiring the engineer who owns this agent end-to-end.
What You’ll Do (representative Projects)
CPI-feedback creative critic loop — Extend our LLM critic + performance-feedback regeneration from images-only to images + video + copy, all closed-loop, all running unsupervised at thousands of variants per day.Video pipeline — Build from a topic + product brief to a platform-ready 9:16 vertical ad — script, scene plan, b-roll, voiceover (ElevenLabs / Hedra), captions — in under 90 seconds per iteration, under $0.50 per iteration.Generative model router — Pick the right model per brief (Flux Schnell vs Pro, Veo 3, Sora, Runway Gen-3/4, Kling, Hailuo), minimizing $/asset under a quality floor. Prove your routing strategy in production via A/B.Policy pre-flight checker — Build a VLM (GPT-4o vision / Gemini / Claude vision) that vets every frame and caption against current Meta / Google / TikTok ad policy before upload. Block 100% of would-be-rejected creatives at the source.Brand-style LoRA / DreamBooth checkpoint — Train and ship on past CPI-winning ads. Deploy serverless on fal / Replicate. A/B against base Flux on real spend.Event-triggered ad pipeline (video) — Earthquake hits at 14:02 → by 14:12 you have 50 paused video variants in Meta and TikTok, each with platform-specific aspect ratios and locale-specific voiceover.
You May Be a Good Fit If
You understand diffusion and video models viscerally — you’ve debugged them, trained a LoRA, optimized inference, built a ComfyUI workflow you’d defend in public.You can name your daily model stack — Flux vs SDXL vs Veo vs Sora vs Runway vs Kling vs Hailuo — and explain when each wins, where each breaks, and what you’d reach for at $0.01/asset vs $0.50/asset.You have public artifacts — a fal demo, a Replicate model, a Civitai upload with >100 downloads, a viral X thread of your generations, a ComfyUI workflow on GitHub. Portfolio matters more than resume.You have scroll-stopping instinct — you know what makes someone not swipe past an ad in the first 3 seconds.You think about cost as a first-class design constraint — $/asset, $/click, $/install. Cost arbitrage between model tiers is something you’ve actually shipped.You’ve read Meta Advertising Standards / TikTok branded-content rules end-to-end — policy is a pre-deploy gate, not a post-mortem.You’re a builder — Idea → working pipeline → first 100 ads shipped → CPI data back → tighter loop. Not “I’ll spec it for Q3.”
Strong Candidates May Also Have
Pretrained or significantly advanced a VLM (not just SFT’d or LoRA’d one).Open-sourced a ComfyUI custom node, a diffusers extension, or a Replicate model with real traction.Deployed serverless inference on fal / Replicate / Modal at scale (>10k req/day).Shipped a video product end-to-end: script → scene plan → b-roll → voiceover → captions → final cut.Authored a public take on generative video model failure modes that other engineers cite.
Not the Right Fit If
You’ve only ever prompted hosted models — you’ve never trained a LoRA, written a ComfyUI workflow, or deployed a custom checkpoint.Your creative experience stops at Photoshop or Canva templates. You can’t tell us why a Flux generation has bad hands or why Veo 3 over-saturates skin.You think “AI creative” means asking GPT to write ad copy.You’re an academic researcher chasing first-author papers. We ship.You’re a brand-side creative director without engineering depth. We need someone who debugged a CUDA OOM at 2am because the generator was holding up the next batch.
How We’ll Evaluate You
Take-home: build a small agentic creative pipeline end-to-end — your call: image-only or short video, hosted or self-served, model of your choice. Walk us through what you built and every model / cost / quality decision behind it. Conversations with the team follow. Portfolio matters more than resume — if you can’t show a public artifact, please come back when you can.
What You Get
Competitive Bay Area comp + meaningful equity.Unlimited generative model budget — fal, Veo, Sora, Runway, ElevenLabs, OpenAI image, Anthropic vision, Hedra, Kling. We expect you to burn through it.
About The Team
You’d join the team building NewsBreak’s agentic growth platform. We already ship a CPI-feedback creative critic loop, event-driven creative pipelines, and multi-platform ad-upload tooling for Meta, Google, and TikTok. Your job: take the creative side from “thousands of images per day” to “video too, smarter every cycle, cheaper every month.”
If you read this and thought “finally, a JD that’s written for me” — we want to talk.
Benefits
We offer a competitive benefits package:
Health, dental, and vision care for you and your family (100% coverage for employee)Top-tier 401(K) plan with company matchingPaid time off and paid holidaysFSA, HSA and commuter benefits programsTeam activity budget
The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process.
Annual Base Pay Range
$120,000—$220,000 USD
CPRA Privacy Notice for California Candidates | full_time | — | false | — | 33 | 2026-06-25T01:23:19.000Z | 2026-07-25T01:23:19.000Z | false | — | — | — | — | — | — | — | — | Mountain View | California | United States | NewsBreak | 335 | 23,855 |
Playground
Run this API
Advanced parameters are collapsed below.
Inputs
Output limits
$1.00 / 1k jobs
Billed per jobs returned — no row cap set
live
curl -X POST https://api.mindcase.co/v1/data/linkedin/jobs/run \
-H "Authorization: Bearer mk_live_YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"params": {
"jobTitles": "",
"locations": "",
"company": [],
"workplaceType": [],
"employmentType": [],
"experienceLevel": [],
"salary": [],
"postedLimit": "",
"sortBy": "",
"industryIds": []
}
}'Edit the form to update this live.
Overview
About LinkedIn Jobs API
LinkedIn Jobs extracts active job postings from a search — job title, company, location, the full job description, salary when listed, applicant counts, and a complete company profile (employee count, follower count, specialities, industries, and office locations).
Recruiters use LinkedIn Jobs to monitor talent demand in specific sectors. Sales teams use it to find companies expanding their engineering or marketing departments to identify high-intent leads.
Real-time dataSelf-servePay per resultZero setup time
Cost
Pricing
$1.00per 1,000 jobs
$1.00 per 1,000 jobs. Each job returned counts as one row. The total scales with the number of job titles and locations you provide multiplied by the results limit per search. Failed runs don't count.
Pay as you goNo subscriptionNo setup feeCancel anytime