Innovation: lead our focused bets on real time adaptation, which include innovating on algorithmic recipes which result in large real time gains.
Cross-Stack Optimization: collaborate across software, hardware, and algorithmic domains to achieve system-wide efficiency gains.
Research & Development: explore new research directions in efficient machine learning, alignment, inference time scaling and adaptable systems. We will have a focus on gradient free techniques which produce large performance gains, as well as data efficient techniques which allow for rapid alignment and adaptation.

Deep expertise in at least one area: model efficiency, distributed systems, hardware acceleration, or algorithmic optimization
Systems thinking ability to understand and optimize across the full ML stack
Strong programming skills in Python. Experience with deep learning frameworks (PyTorch, JAX, TensorFlow)
Knowledge of model optimization techniques (RLHF, finetuning)
Experience in an industry lab with computing at scale and/or fast-paced startup environment
Nice to have: PhD in computer science, and experience with algorithm design

Flexible work: In-person collaboration in the Bay Area, a distributed global-first team, and quarterly offsites.
Adaption Passport: Annual travel stipend to explore a country you've never visited. We're building intelligence that evolves alongside you, so we encourage you to keep expanding your horizons.
Lunch Stipend: Weekly meal allowance for take-out or grocery delivery.
Well-Being: Comprehensive medical benefits and generous paid time off.

Efficiency Research Engineer

Key skills