avride · Austin, Texas
Skills: Python, SQL, AWS, Docker
About the Team Avride is at the forefront of autonomous mobility, developing and deploying self-driving cars and delivery robots that are shaping the future of transportation and logistics. Our Labeling Backend team builds the data infrastructure behind the massive sensor datasets that power our perception and ML pipelines. The services we build support both automated and human-in-the-loop labeling workflows, delivering the high-quality labeled data our models depend on so our vehicles and robots keep improving at scale. About the Role As a Labeling Backend Software Engineer, you will own backend services that handle massive datasets for our perception ML pipelines. You’ll work across APIs, data ingestion pipelines, databases, and orchestration frameworks, taking features from design doc to production and keeping them reliable, high-throughput, and maintainable once they’re live. You’ll operate independently, make architectural tradeoffs, and help raise the bar for the engineers around you. This is a hands-on individual contributor role: you will spend most of your time designing, writing, and shipping code. What You’ll Do Design, build, and own backend systems that manage the full lifecycle of labeled data, from ingestion to delivery, including core Python services, APIs, and databases. Build and scale data preparation and labeling pipelines that transform massive sensor streams (lidar, camera, radar) into label-ready formats, and manage annotation workflows at scale using both automated and human labeling with modern orchestration frameworks. Design and implement robust integrations with external vendors and internal tools so data and feedback flow seamlessly across labeling workflows. Develop automated validation an …truncated… lt;li>Production experience with relational databases (preferably PostgreSQL): schema design, query optimization, ORMs (e.g., SQLAlchemy, Django ORM), and migrations (e.g., Alembic). Solid grounding in system design, algorithms, and data s…
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