Labeling Backend Software Engineer

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 and QA systems that safeguard dataset integrity, monitor quality, and surface key performance insights.
• Partner with ML and Perception teams to turn evolving requirements into scalable data solutions that directly drive model improvements.
• Increase human labeling efficiency by integrating ML automation into annotation workflows.
• Lead technical design for your area, review code, and mentor other engineers on the team.

What You'll Need

• 4+ years of professional software engineering experience building and operating backend services in production (internships and academic projects don't count toward this).
• A track record of owning services end-to-end: design, implementation, deployment, monitoring, and on-call.
• Strong proficiency in Python, including backend frameworks and asynchronous stacks (asyncio, aiohttp, FastAPI).
• 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 structures, applied to real systems at scale.
• Hands-on production experience with cloud platforms, containerization (Docker, Kubernetes), and cloud object storage (AWS S3, GCS, etc.).

Nice to Have

• Experience with workflow orchestration (Argo, Airflow, etc.)
• Experience with large-scale distributed systems or products
• Big data and distributed data-processing tooling (Spark, PyArrow, etc.)
• Experience working with 3D sensor data (point clouds, sensor fusion, etc.)
• Previous work in AV, robotics, or ML-heavy environments
• C++ development experience

Additional information

Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.