Senior Ai Engineer

HyperFi AI Inc

San Francisco, CA, United States
On-site
End-to-end ai program ownership
Model selection and routing
Gpu architecture definition
Own our AI program end-to-end, defining how models are selected, trained, tuned, routed, and evaluated

Job Summary

  • Own our AI program end-to-end, defining how models are selected, trained, tuned, routed, and evaluated.
  • Define the GPU architecture and lead the fine-tuning strategy, focusing on LoRA and cost-effective GPU spend.
  • Build agentic LLM pipelines, construct RAG systems, and instrument evaluation metrics to guide model evolution.

Matching Summary

Own our AI program end-to-end, defining how models are selected, trained, tuned, routed, and evaluated.

Skills & Requirements

Must-have

  • End-to-end AI program ownership
  • Model selection and routing
  • GPU architecture definition
  • Agentic LLM pipelines
  • Retrieval-augmented generation (RAG) systems

Nice-to-have

  • Prompt engineering and context design
  • Model evaluation and telemetry
  • Integration with user-facing flows
  • Experience with OSS tools

Key Requirements

  • 8+ years building production-grade ML systems
  • Hands-on model training and fine-tuning
  • Confidence in GPU architecture definition
  • Strong Python skills
  • Senior IC judgment

Work Rights

Not specified

Tailored Resume

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