Research Scientist - Human-AI Systems
About The Position
About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. 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.
Requirements
- 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.
Nice To Haves
- Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.
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.
Benefits
- market proven solutions
- robust funding
- scaling rapidly
- meaningful opportunities to shape priorities and initiatives
- influence key strategic decisions
- directly impact our ongoing success
- deepen your technical expertise
- explore leadership opportunities
- learn new skills across multiple functions
- supported in building your career in an environment designed for growth, learning, and shared success
- Equal Employment Opportunity employer
- building a team that represents a variety of backgrounds, perspectives, and skills
- embraces diversity and provides equal employment opportunities to all employees and applicants for employment
- 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.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
