Machine Learning Engineer, II - Annotation Automation

Torc Robotics • Ann Arbor, MI

4h

About The Position

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
We are the annotation automation team, dedicated to accelerating the creation of high-quality ground truth through auto-labeling. To support ML model development for self-driving, we build pipelines that produce clean, balanced, and annotated datasets. The team develops and maintains large-scale pipelines for camera/lidar object detection, tracking, fusion, and HD map creation, deploying these solutions on AWS to process massive sensor data streams.

Requirements

• Bachleor's or Master’s degree in Computer Science, Computer Engineering, Robotics, or a related technical field.
• 2+ years of professional working experience in a relevant field (Autonomous Driving, Robotics, or Computer Vision).
• Coding Proficiency: Strong Python or C++ skills with a solid understanding of data structures and algorithms.
• ML Frameworks: Practical experience with at least one deep learning framework, such as PyTorch or TensorFlow.
• Computer Vision: Foundational knowledge of computer vision tasks (e.g., object detection, segmentation, or tracking).
• Problem Solving: Ability to take a well-defined technical problem and drive it to completion with limited supervision.
• Communication: Good communication skills, with the ability to explain technical work clearly to teammates.

Nice To Haves

• Cloud Experience: Familiarity with AWS services (S3, EC2, SageMaker).
• 3D Perception: Experience working with Lidar point clouds or sensor fusion.
• Optimization: Exposure to DNN model optimization tools like TensorRT or ONNX.
• Hands-on Projects: A portfolio of ML projects or contributions to open-source robotics/CV libraries.

Responsibilities

• Implement and Test: Execute the development and testing of offline object detection, tracking, and fusion modules to generate annotations from logged sensor data (Cameras, Lidars, Radars).
• Pipeline Maintenance: Support and enhance existing auto-labeling pipelines on AWS, ensuring they meet quality and performance standards for various use cases.
• Optimization: Assist in the deployment and performance tuning of cloud-based ML pipelines to improve data throughput.
• Data-Centric AI: Contribute to the development of data-centric AI workflows, focusing on data quality and model uplift.
• Collaboration: Participate in technical discussions, brainstorming sessions, and team meetings to share progress and resolve blockers.
• Documentation: Create and maintain clear documentation for tools, workflows, and experiments to ensure team scalability.

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)
• AD+D and Life Insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level