Woven by Toyota
Software Engineer II, Data Labeling
About this role
Woven by Toyota seeks a Software Engineer II to design and operate scalable production pipelines that convert autonomous vehicle sensor data into labeled datasets and HD map features for ML model training. You'll work at the intersection of data engineering and geospatial algorithms, collaborating with perception and ML teams to deliver high-quality structured data for autonomous driving development.
What you'll do
- Build and maintain scalable production pipelines for auto-labeling and data processing workflows
- Develop data validation and quality assurance systems to ensure high-quality labeled datasets
- Collaborate with perception and ML teams to understand data requirements and deliver actionable insights
- Own end-to-end components of labeling infrastructure, from sensor data ingestion to final delivery
- Implement workflow orchestration and geospatial algorithms for HD map feature generation
- Provide data science insights to support autonomy development and model evaluation
What they're looking for
- Data pipeline and ETL development
- Workflow orchestration and scheduling
- Geospatial data processing and algorithms
- Python or similar backend programming languages
- Database and data warehousing experience
- Quality assurance and validation systems design
- Cloud infrastructure and distributed systems
- Autonomous vehicle domain knowledge (preferred)
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Woven by Toyota
Woven by Toyota develops software-defined vehicle platforms and AI solutions, with a focus on autonomous driving systems and secure, human-centric mobility technology. The company is hiring Systems Engineers and Software Engineers to architect platforms, design software systems, and build sensor calibration tools for next-generation vehicles.
- Website
- woven.toyota
Likely interview questions
- Describe your experience building and scaling data pipelines—what challenges have you encountered and how did you solve them?
- How have you approached end-to-end ownership of a complex system, and what did you learn from that experience?