ML Engineer
Core
Build the AI layer's learning loop for a robotics data platform, focusing on evaluations, retrieval, and cost-optimized inference for robot fleet data.
Role type
Applied ML Engineer (LLM systems & robotics data)
Builds
AI agents, evaluation systems, retrieval pipelines, and task-specific models for robot fleets
Domain
Robotics, AI/ML, Data Infrastructure
Deliverable
production ML models
Required skills
Applied ML, LLM systems (evals, retrieval, fine-tuning), Python for production, measurement-driven development
Preferred skills
Custom model training (embeddings, fine-tunes), time-series/sensor data experience, inference cost optimization at scale, open-source contributions
Technologies
Python, LLM frameworks, robotics data stacks
Responsibilities
Build evaluation systems for quality, speed, and cost; optimize retrieval over messy fleet data; reduce inference costs via routing, caching, and distillation; train task-specific models; convert cross-fleet usage into improving datasets and detectors
Seniority
Mid-level, hands-on IC