Software Engineer, Data Platform

Job description

Job responsibilities

• Build data ingestion pipelines from multiple sources, including our own field capture and teleop stacks
• Build automatic data validation systems that catch quality issues before data reaches annotation or training
• Build and improve annotation ingestion, tooling, and workflows to increase labelling efficiency and throughput
• Own data quality and diversity — build the systems and metrics that tell us what data we have, what's missing, and where to focus collection
• Explore and build automated annotation methods, including running computer vision and vision-language models for tasks like depth estimation, hand tracking, and auto-labeling, to reduce manual labelling load over time
• Support the platform — debug issues in live pipelines, instrument for observability, and work directly with research and annotation partners who depend on your software

Job requirements

• 2+ years of software engineering experience building production systems
• Strong programming fundamentals and comfort working across the stack — services, data pipelines, and applied ML tooling
• Experience with at least one of: real-time or large-scale data pipelines, ML data workflows, computer vision, or data infrastructure
• Bias for ownership: you've taken features or systems from prototype to production and supported them in the field
• Clear communication and close collaboration with product, research, and annotation/operations partners
• Hands-on experience with sensor data (video, depth, IMU, force/torque) and the infrastructure to process, validate, and label it at scale is a plus
• Experience with streaming or near-real-time data pipelines is a plus
• Familiarity with ML data workflows (datasets, labelling, evaluation) is a plus