Senior Software Engineer - ML Data Delivery

Role Description

The Pseudo-Labeling team's goal is to create high-quality annotations on sensor data (images, point clouds). The annotations include:

• 2D, 3D bounding boxes
• Classes
• Trajectories
• Lane lines
• Segmentations
• Depths

This role sits at the intersection of that pseudo-labeling data and the online perception team, building the systems that select, package, and deliver the right data to feed on-demand model training.

What You'll Do:

• Design, implement, test and deploy tooling and pipelines for internal quality control and issue identification of pseudo-labeled data.
• Provide statistical support and report on pseudo-label quality, coverage, and pipeline health to internal stakeholders and leadership.
• Support secondary data selection (virtual packaging) to curate and feed on-demand data to online model training.
• Support the build-out of the ML data delivery system that enables the online perception team to train models on-demand.
• Drive general pipeline improvement and optimization across the pseudo-labeling and data delivery stack.
• Demonstrate project management skills, serving as project lead guiding less experienced team members.
• Stay up to date with the latest developments in offline perception, data pipeline engineering, and ML data infrastructure for autonomous driving.
• Independently develop tools, services, and algorithms using disciplined software development processes.
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets.
• Proactively assess current capabilities to identify areas for improvement.
• Guide and produce information products, supporting visualization and data accessibility.
• Evaluate and make recommendations regarding technical advances.
• Develop guidelines and standards for data quality control and data delivery systems.
• Provide technical guidance or business process expertise to team members.

Qualifications

• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision.
• Expected to drive alignment across team interfaces to the rest of the organization.
• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus 6+ years of experience OR;
• Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus 3+ years of experience OR;

Requirements

• Familiarity with the offline perception stack and knowledge of how pseudo-label data is produced.
• Strong software engineering background building and operating data pipelines and services at scale.
• Statistical analysis and reporting skills, with the ability to translate data quality findings into actionable insights.
• Scaled ML Operations (MLOps) and Tooling – ML Frameworks, experiment tracking, model registry.
• Model Data Curation – Parquet data processing (PyArrow, Daft, Pandas, etc).
• Proficiency in Python software development and experience with VDI and cloud-based development environments.
• Experience with distributed data processing and/or ML frameworks – PyTorch, Lightning, Ray, or similar.

Benefits

• A competitive compensation package that includes a bonus component and stock options.
• 100% paid medical, dental, and vision premiums for full-time employees.
• 401K plan with a 6% employer match.
• Flexibility in schedule and generous paid vacation (available immediately after start date).
• Company-wide holiday office closures.
• AD+D and Life Insurance.