Torc is looking to develop software for automated trucks to transform how the world moves freight, and the Pseudo-Labeling team's goal is to create high-quality annotations on sensor data for use by downstream users such as perception teams and simulation teams.
Requirements
- Active Learning & Pseudo-labeling - Computer Vision, Deep Learning, Model training
- Two of the following: 2D/3D Object Detection, Tracking, Sensor Fusion, Semantic Segmentation, SLAM, BEV
- Scaled ML Operations (MLOps) and Tooling – ML Frameworks, experiment tracking, model registry, MLFLow, Weights and Biases, ML Metrics and Evaluation / Quality
- Distributed machine learning frameworks - PyTorch, Lightning, Ray
- Model Data Curation - Parquet data processing (PyArrow, Daft, Pandas, etc)
- Development Tools & Eco-System (at scale) - Proficiency in Python software development
- VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker
Responsibilities
- Design, implement, test and deploy offline object detection, tracking and fusion modules to automatically create annotations on Cloud Services from logged sensor data (Cameras, Lidars, Radars)
- Independently develop offline perception models or algorithms using disciplined software development processes
- Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows
- Measure and track auto labeling quality to meet internal customer requirements
- 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 analytics and machine learning models, their deployment, and associated processes
Other
- Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 6+ years of experience
- Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 3+ years of experience
- Demonstrated project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution
- Ability to work with wide latitude for independent judgment
- Ability to drive alignment across team interfaces to the rest of the organization
