Data Engineer (Robotics)

Location: San Francisco, United States; on-site

Company

Builds autonomous, zero-emissions haulers using vision-based AI to reduce freight costs across global logistics networks.

What you will do

• Build and maintain pipelines for ingesting, validating, and processing multimodal vehicle sensor logs.
• Design schemas and data models for discovering and querying driving data used in ML training, evaluation, and debugging.
• Transform raw driving data into derived signals, annotations, and aggregates for downstream teams.
• Develop data loaders, query interfaces, and dataset assembly utilities used across the organization.
• Collaborate with ML, vehicle software, curation, and fleet operations to support the flow from data collection to model training.
• Help design a data stack that scales with the engineering team and vehicle fleet.

Requirements

• BS, MS, or PhD in Computer Science, Engineering, Robotics, or a related field, or equivalent industry experience.
• Strong Python proficiency and ability to write maintainable code.
• Solid database fundamentals and experience designing adaptable schemas.
• Understanding of how ML training pipelines consume data.
• Experience with large codebases and modern build and development environments such as Bazel, monorepos, or dev containers.
• Must be eligible to work in the United States and work on-site in San Francisco.

Nice to have

• Experience with autonomous vehicles, robotics, or similar data environments.
• Familiarity with Foxglove, rerun, or comparable visualization and data-platform tools.
• Experience with data catalogs, metadata stores, or feature stores.
• Experience handling high-volume video, point-cloud, and time-series data at terabyte-plus scale.
• Cloud data engineering experience with GCP or AWS.

Culture & Benefits

• Fast-moving, close-knit environment with autonomous-vehicle industry experience.
• Early-team setting with high ownership, low ego, and fast iteration.
• Pragmatic approach focused on learning unfamiliar tools and reasoning from first principles.

Hiring process

• Interview process may include AI-assisted comparison of qualifications and experience.
• A human reviews AI output and makes the final hiring decision; eligible applicants may have a legal right to opt out of AI use.