As a Data Scientist for Llama Scalability (Technical Leadership) at Meta, you will collaborate on a wide array of product and technical problems with cross-functional partners. Your focus will be on using data and analysis to identify and solve challenges in developing foundational AI models, particularly in scaling up evaluation, improving efficiency, and building privacy systems for Llama models.
Key responsibilities include:
- Working with large, complex datasets to solve challenging problems using various analytical and statistical approaches.
- Applying technical expertise in quantitative analysis, experimentation, and data mining to develop strategies for products serving billions.
- Identifying and measuring product success through goal setting, forecasting, and monitoring key metrics.
- Defining and testing opportunities to improve products, driving roadmaps through insights and recommendations.
- Partnering with Product, Engineering, and cross-functional teams to inform and execute product strategy.
You'll be part of the Research Pillar in the AI Foundations pillar within the Gen AI product group, owning the development of state-of-the-art Gen AI technology. This role is crucial in Meta's 2024 objective to become the leader in AI, working closely with Llama Research Scientists to build expertise in LLM training and unlock Meta's key advantages in this space.
The ideal candidate will have:
- 10+ years of experience in Product Data Science, including in-depth experimentation experience.
- Strong skills in data querying (e.g., SQL), scripting (e.g., Python), and statistical software.
- Excellent framing and communication skills.
- Proven intellectual curiosity and ability to handle ambiguity and complexity.
- Experience with AI, LLM, machine learning, and experimentation methods (preferred).
- A Bachelor's degree in a relevant technical field, with a Masters or Ph.D. preferred.
Join Meta to shape the future of AI and be part of a world-class analytics community dedicated to skill development and career growth.