Data Scientist, GenAI
Bellevue, WA | Menlo Park, CA | Seattle, WA | New York City | San Francisco, CA
One of our company priorities is to lead in AI by developing market-leading models across modalities (text, photo, video, voice). A crucial ingredient for success is being able to understand how our models are performing – to benchmark against competitors, understand performance wins and gaps so we can adjust training/development, inform leadership investment decisions, support open-source rollouts, etc. As we scale and develop models with capabilities across modalities, there is a huge amount of work needed to improve our evaluations framework. This DS will lead that work with partners in Research, Infra, Policy to both operationalize and scale our existing model evaluations so they are easily reproducible, and to develop new frontier evaluations to help us measure new capabilities.
You will be part of the AI Foundations pillar within the Gen AI product group. This team owns both developing foundational State of the Art Gen AI technology.
Product leadership: You will use data to shape development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product’s ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won’t simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.Data Scientist, GenAI Responsibilities
- Leverage internal tools and external APIs to run existing evaluations on Llama models and key competitors to benchmark our performance against the competition.
- Work to operationalize and standardize the evaluation process to make it faster and more reliable. Consult with DE on data infra/dashboarding and building eval datasets
- Extract insights from evaluations and competitor comparisons to feed back into model training and development
- Work with research to develop new frontier evals, both to measure new modalities/capabilities (e.g., agentic models, speech generation, video generation) and to better assess core existing capabilities like coding, math, general knowledge
- Do foundational work to assess how we can measure AGI
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 7+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
- Experience working effectively with multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
- Experience framing and communication skills
- Intellectual curiosity and drive, decisiveness, with ambiguity and complexity
- Experience doing product analytics on consumer facing digital products, or working on AI Infra and Privacy related products.
- Experience working with researchers and infrastructure teams.
- Experience with Python.
- Experience with predictive modeling, machine learning, and experimentation/causal inference methods.
- Masters or Ph.D. Degree in a quantitative field
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Tags: AGI APIs Causal inference Computer Science Engineering Finance Generative AI LLaMA Machine Learning Mathematics Model training Open Source Physics Predictive modeling Privacy Python Research VR
Perks/benefits: Career development Equity / stock options Health care Salary bonus
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