Research Scientist - Human-AI Systems
About this role
Professionals who enjoy turning research into reusable, scalable systems and want to advance frontier AI through data and environment creation will thrive in this position. The team at Snorkel AI builds datasets, benchmarks, evals, and custom solutions for real-world AI systems by combining technology with research-driven AI data development. This researcher will design and optimize pipelines that integrate real-world data, automated generation, and human expert input to target frontier model performance gaps.
This role exists to amplify human knowledge and judgment, enabling experts to create and refine data and agentic environments that strengthen the company's position as a frontier data lab. The incoming scientist will collaborate closely with engineering, product, data operations, academic partners, and enterprise customers to scale these workflows. Candidates with a strong background in artificial intelligence, machine learning, or natural language processing who feel comfortable navigating ambiguous research questions and rapid iteration will find a suitable home here.
What you will do
- Design, implement, and optimize reusable pipelines that combine artificial intelligence capabilities with expert judgment to accelerate the creation of data and agentic environments.
- Design and execute rigorous experiments to validate proof-of-concept approaches, measuring their impact on data quality, pipeline efficiency, and model performance.
- Collaborate with engineering, data operations, domain experts, and customers to transition research prototypes into reliable production workflows.
- Work directly with domain experts to design and test workflows that facilitate the authoring, reviewing, and refining of data and environments.
- Partner cross-functionally with data operations, product, and engineering teams to share research findings that inform the company roadmap.
- Maintain awareness of frontier research in data and agentic environment creation while integrating best practices into existing workflows.
- Represent company research externally via publications, blog posts, conference talks, and customer engagements.
What you need
- Demonstrate a strong research background in artificial intelligence, machine learning, natural language processing, large language models, or related fields with experience developing and evaluating new methods.
- Bring experience building environments for AI agents across automated research, computer use, coding, or professional domain workflows.
- Possess hands-on experience with synthetic data generation, human-in-the-loop workflows, reinforcement learning, agent environments, or model evaluation.
- Apply strong experimental design skills, including defining hypotheses and conducting ablations.
- Utilize software engineering best practices such as clean coding, modular design, and version control.
- Translate domain expert knowledge into concrete tasks, evaluation criteria, and repeatable workflows through effective collaboration.
Nice to have
- Ph.D. in machine learning, NLP, or a related field
Skills and tech stack
Questions candidates ask
What locations are available for this position?
The job location is available in San Francisco, New York, or remotely.
What is the compensation range for this role?
The salary range for this position is $200,000 to $375,000 USD, with actual compensation determined by skills, qualifications, experience, and geographic location.
What kind of teams will I work with?
You will collaborate with domain experts, academic partners, customers, and internal product and engineering teams.