Snorkel AIResearch Lead, Open Benchmarks Grants
Snorkel AI is hiring a Research Lead, Open Benchmarks Grants in New York and San Francisco, United States. Level rates it ; you can apply on Snorkel AI.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting allows some remote work.
- Tools and skills the posting cites include AI evaluation and NLP.
- Level lists 41 other open roles at Snorkel AI.
- The role was posted in the last few days.
AI in this role
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!
ABOUT THE ROLE
We're looking for a Staff or Senior Research Scientist to collaborate with partners and lead the development of the next frontier benchmarks and datasets. This is a highly visible, customer-facing role at the intersection of research, company strategy, and go-to-market. You'll design datasets taking into account frontier model performance and work with our academic partners, and then partner with delivery, product and go-to-market to scale out production. You will also serve as a credible technical partner for our customers, prospects, and drive results that impact the broader research community.
This role reports directly to the Head of Research and is ideal for someone who is energized by cross-functional work and wants to understand how startups operate across research, data operations, and commercial teams.
MAIN RESPONSIBILITIES
- Design state of the art datasets that drive frontier model training and evaluation based on current model performance and academic partnerships
- Translate benchmark insights into clear, compelling narratives that articulate the ROI of expert-curated data for customer-facing presentations, technical reports, and go-to-market materials.
- Work cross-functionally with data operations, product, engineering, and strategy to surface research findings that inform the company roadmap.
- Stay at the frontier of LLM evaluation research 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/ML evaluation, NLP, or related fields, with a track record of rigorous experimental design — especially around measuring the impact of training and evaluation data on model behavior.
- Exceptional communication skills — able to present complex technical findings clearly to both technical and non-technical audiences
- Comfort operating in a fast-moving, cross-functional environment with ambiguous problem spaces
- Genuine interest in GTM strategy, startup dynamics, and the commercial side of AI data services.
- Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.
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.
How we rate this
Research Lead, Open Benchmarks Grants at Snorkel AI rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Evaluation and NLP. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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