Data Adaptation Research Engineer improving real - time adaptive algorithms. Collaborating on innovative data strategies for malleable data spaces and efficient AI systems in a global - first team.
About the role
- Efficiency Research Engineer leading real-time adaptation innovations in AI systems. Collaborating on algorithms for efficiency gains across software, hardware, and algorithms.
Responsibilities
- 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.
Requirements
- 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
Benefits
- 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.
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