Senior Autonomy Engineer (Data Curation)

About the role

Join our team as a Senior Autonomy Engineer, where you will play a crucial role in building a data flywheel for our autonomy initiatives. You will collect and curate high-quality datasets from internal and external drone fleets, enabling our Autonomy teams to train and develop models effectively. This is an individual contributor role reporting to the Director of Autonomy Data Curation. Your responsibilities will include building and operating data transformation pipelines, improving dataset quality and repeatability, and applying privacy and security requirements throughout our processes. You should have at least 5 years of professional software engineering experience, hands-on experience building data pipelines for large-scale datasets, and a strong proficiency in programming. Key missions: Collect and curate high-quality, model-ready datasets from internal and external fleets of drones for training and model development.. Build and operate pipelines that transform raw autonomy logs and media into curated datasets with strong observability and clear ownership.. Develop tooling that makes data discovery and slicing fast and self-serve for Autonomy teams, improving dataset quality and repeatability. Profile: - Experience with data modeling, schema evolution, and dataset/version management - 5+ years of professional software engineering experience (or equivalent), with significant ownership of production systems - Hands-on experience building data pipelines for large-scale datasets (ETL/ELT, streaming or batch, orchestration) - Strong proficiency in programming, demonstrable in at least one of of our most frequently used languages (Python/C++) - Solid understanding of reliability engineering: monitoring, incident response, backfills, and operational rigor - Ability to work across ambiguous interfaces (data + tooling + model consumers) and drive decisions - Experience with autonomy/robotics data: flight logs, self-driving car data, sensor fusion traces, video, geospatial metadata - Experience with labeling workflows, annotation tooling, and labeling QA at scale - Familiarity with privacy concepts (PII handling, redaction, access control, audit logs) - Experience with vector/semantic search over media or telemetry - Experience building hard-mining evaluation loops for ML models