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.
About the role
- 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.
Responsibilities
- Innovation: lead focused bets on data adaptation by developing algorithmic recipes that dramatically improve data quality, downstream performance, and efficiency.
- Research & Development: explore new directions in data adaptation across modalities and lifecycle stages, bridging cutting-edge AI research with practical applications in real-time intelligence.
- Hands-on Impact: shape the data landscape for intelligent, adaptable AI agents by guiding Adaption's data strategy and creatively solving novel challenges in data, interaction, and evaluation.
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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