Senior, Software Engineer - ML Data Delivery

Torc Robotics, a leader in autonomous driving technology since 2007, is focused on developing software for automated trucks. The Senior Software Engineer - ML Data Delivery will be responsible for designing and implementing tooling and pipelines for quality control of pseudo-labeled data, supporting the online perception team, and driving improvements across data delivery systems.

Responsibilities:

• Design, implement, test and deploy tooling and pipelines for internal quality control and issue identification of pseudo-labeled data, ensuring annotations meet the bar required by downstream model training
• 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, identifying and resolving bottlenecks in throughput, quality, or reliability
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution
• 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, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining documentation of created applications
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics and ML training workflows
• Proactively assess current capabilities to identify areas for improvement, proposing solutions that align with core strategy and operation
• Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner
• Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety
• Develop guidelines and standards for data quality control, data delivery systems, and their deployment, and associated processes
• Provide technical guidance or business process expertise, technical leadership, coaching and mentoring to team members

Requirements:

• Bachelor's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrated competencies and technical proficiencies typically acquired through 6+ years of experience OR
• Master's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrated competencies and technical proficiencies typically acquired through 3+ years of experience OR
• Familiarity with the offline perception stack in general, and knowledge of how pseudo-label data is produced and related best practices
• 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, MLflow, Weights and Biases, ML Metrics and Evaluation / Quality
• Model Data Curation – Parquet data processing (PyArrow, Daft, Pandas, etc)
• Development Tools & Eco-System (at scale) – Proficiency in Python software development. Also, VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker
• Experience with distributed data processing and/or ML frameworks – PyTorch, Lightning, Ray, or similar
• Experience with large-scale data delivery systems and associated quality control
• Pseudo-labeling experience in general