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
- Interface Research Engineer in hybrid role at AI company innovating adaptive intelligence through algorithm design and feedback mechanisms. Collaboration across software, hardware, and algorithmic domains for efficiency gains.
Responsibilities
- Innovation: innovate on our product to co-design algorithms that react real-time to product signal and feedback. Design new ways of giving feedback that drive better algorithms.
- Cross-Stack Optimization: collaborate across software, hardware, and algorithmic domains to achieve system-wide efficiency gains
- Measure what matters: we believe strongly that the ultimate signal of value is whether we have real world impact. Our current algorithms are capable of interacting with the world which is why product matters so much.
Requirements
- Deep expertise in at least one area: model efficiency, real time alignment 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)
- A plus is experience in an industry lab with computing at scale
- A plus is a PhD or equivalent research experience in a computer science field
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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