
Posted 14 days ago
Autonomy Engineer, Data
AI Summary
Builds data pipelines and dataset tooling that ingest, process, enrich and organize vehicle sensor recordings so ML models for autonomous vehicles can be trained, evaluated and debugged. Works in-office in San Francisco with ML and vehicle software engineers.
About this role
About Humble Robotics
Working at Humble Robotics means taking on the biggest change in ground transportation in decades. We're building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today's global logistics network.
We're a fast-moving, close-knit team of AV industry veterans and innovative thinkers. We don't believe culture can be engineered – but when it falls into place, it's a once-in-a-lifetime adventure.
Progress has never felt so present.
About The Role
We’re looking for an engineer to join our autonomy team and build the data systems that help our vehicles learn from real-world driving. Working directly with ML and vehicle software engineers, you’ll turn sensor recordings into reliable datasets for model training, evaluation, and debugging.
Your work will drive the autonomy flywheel: turning driving experience into useful training data, enabling better models, and helping the team understand where to improve next. You’ll build software across data ingestion, processing, enrichment, and dataset tooling, with initial projects shaped around your strengths and interests.
We welcome early-career engineers with strong software fundamentals and substantial hands-on work through internships, research, open-source contributions, or personal projects.
What You’ll Do
- Work as part of the autonomy team to build the data workflows behind model development, evaluation, and iteration.
- Build and maintain pipelines that ingest, validate, and organize vehicle sensor recordings in our data lake.
- Develop processing workflows that enrich raw recordings with derived signals, perception labels, and road representations.
- Build tools to find, assemble, and load datasets for ML training, evaluation, and debugging.
- Run and improve backfills and reprocessing workflows as algorithms, processing steps, and dataset requirements change.
- Evolve schemas and implement migrations that keep existing data usable as the system develops.
- Investigate data quality issues, processing failures, and performance bottlenecks.
- Collaborate with autonomy teammates to understand their data needs and improve the tools that support them.
What You Bring
Bonus Points
Compensation
Perks and Benefits
Skills
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