The job, in the employer's words
About Snorkel
Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes.
Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab.
This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems.
Location: San Francisco, New York City, OR REMOTE
Main Responsibilities
- Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation.
- Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communicate findings.
- Partner with engineering, data operation, domain experts, and customers to turn research prototypes into reliable production workflows.
- Work directly with domain experts to design and test workflows that help them author, review, and refine data and environments.
- Work cross-functionally with data operations, product, and engineering to surface research findings that inform the company roadmap.
- Stay at the frontier of research in data and agentic environment creation and bring best practices into Snorkel's workflows.
- Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI.
Preferred Qualifications
- Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods.
- Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows.
- Experience with one or more of synthetic data generation, human in the loop workflows, reinforcement learning, agent environments, or model evaluation.
- Strong experimental design skills, including defining hypotheses and conducting ablations.
- Experience with software engineering best practices (e.g., clean coding, modular design, version control).
- Ability to collaborate with domain experts and translate their knowledge into concrete tasks, evaluation criteria, and repeatable workflows.
- Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production.
- Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.
Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Requirements mentioned
- Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods.
- Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows.
- Experience with one or more of synthetic data generation, human in the loop workflows, reinforcement learning, agent environments, or model evaluation.
- Strong experimental design skills, including defining hypotheses and conducting ablations.
- Experience with software engineering best practices (e.g., clean coding, modular design, version control).
- Ability to collaborate with domain experts and translate their knowledge into concrete tasks, evaluation criteria, and repeatable workflows.
- Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production.
- Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.
- Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.
- Salary range(s) for this role
- $200,000—$375,000 USD
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