Research Scientist / Engineer – Foundation Model: Core Research
Luma · San Francisco Bay Area · 1 wk ago
HybridEngineeringFull-time
What You'll Do
- Drive the core research that powers all of Luma's products — co-designing multimodal representations, advancing core algorithms for long-context training, and establishing rigorous scaling laws to predict performance across compute budgets.
- Closely align research with user experience by developing proxy tasks and automated metrics that serve as the compass for research decisions.
- Build the engine for high-velocity research, maintaining production-research parity, ensuring reproducibility, and designing systems for rapid experimentation.
Who You Are
- A Bachelor's, Master's, or PhD degree in Computer Science, Machine Learning, Physics, or Mathematics is essential.
- A 'first-principles' intuition for scaling. You don't just follow the literature; you understand why certain architectures succeed or fail at scale.
- Fluent in the language of frontier AI. You see research and engineering as a single, unified discipline.
- Proven ability to design and rigorously analyze experiments and to articulate complex technical concepts effectively.
- Past experience with distributed or high-performance computing environments, particularly managing and optimizing training runs on large-scale GPU clusters.
What Sets You Apart (Bonus Points)
- A track record of publishing at top-tier venues (NeurIPS, ICML, ICLR).
- A mission-driven, "first-principles" mindset.
- Infrastructure Expertise: Proven ability to build and lead research infrastructure for technical teams, ensuring production-research parity.
- Engineering Excellence: Strong commitment to software engineering best practices, including optimizing for code readability and reusability, implementing comprehensive unit and integration tests, and maintaining high documentation standards (necessary docstrings).
- Experience with low-precision training and hardware-aware optimization for next-gen clusters.