About the position
As the data engine team, our goal is to provide a central data and machine learning platform that can be used across all verticals of the company. We’re looking for generalist engineers that want to build the foundations of a new workflow that spans: Data ingestion from a production fleet, Data processing and storage (TBs/car/day), Labeling infrastructure, Machine learning infrastructure. This group has a massive scope to define how product verticals across the company are deployed at scale for our customers given data and machine learning infrastructure is at the heart of the autonomy problem. We’re still very early in development so if you are interested in the “0-1” stage of building up a new team that interacts with teams across the company, this is a good fit.
Responsibilities
- Design and build large-scale data platforms to support our AI research and autonomy stack development, handling petabytes of multimodal sensor data from real-world driving scenarios
- Work on data curation and tagging platforms that enable efficient dataset discovery, labeling workflows, and quality assessment across diverse driving conditions
- Build high-performance data processing systems using modern distributed computing frameworks to transform raw sensor data into training-ready formats
Requirements
- Strong backend engineering experience
- Problem-solving skills and experience working with cross-functional teams in fast-paced environments
Nice-to-haves
- Hands-on experience with modern data stack technologies including Apache Spark, Hudi, Trino, Kafka, or similar distributed data processing frameworks
- Knowledge of data lake architectures, streaming systems, and workflow orchestration platforms like Flyte
Benefits
- Base salary, equity, and benefits
- Comprehensive health, dental, vision, life and disability insurance coverage
- 401k retirement benefits with employer match
- Learning and wellness stipends
- Paid time off
