As a ML Applied Scientist, you will:
- Become intimately familiar with product use cases, requirements, and data to develop the insights required for solving hard evaluation problems.
- Develop models and systems that reliably solve complex evaluation problems.
- Develop and refine benchmarks that help feature engineers advance the state-of-the-art.
- Research and develop methodological innovations that advance the state-of-the-art in AI evaluation.
- Collaborate on an applied R&D team that is oriented around principles of continuous delivery, iterative development, and fault tolerance.
Minimum Qualifications:
- 6+ years of relevant industry experience with a bachelor’s degree; or 4+ years with a master’s degree; or a PhD 3+ years industry experience; or equivalent work experience.
- Substantive experience solving real-world problems with LLMs.
- Experience with LLM benchmarking and evaluation.
- Experience applying software engineering best practices to ML development.
- Strong research fundamentals.
- Substantive experience with one or more LLM training or post-training paradigm.
- Experience with PyTorch and/or MLX.
