Machine Learning Engineer, II - 3D Perception

Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The Machine Learning Engineer II – 3D Perception will develop, evaluate, and improve production machine learning solutions for Bird's Eye View perception, using multi-modal sensor data to support environmental understanding and autonomous driving system performance.

Responsibilities:

• Design, develop, and improve machine learning models supporting Torc's perception systems
• Own model development and delivery for well-defined perception problem areas, from data preparation and training through evaluation and integration
• Write production-quality Python and PyTorch code to support scalable training, evaluation, and inference workflows
• Analyze model performance, identify failure modes, and independently troubleshoot issues to improve robustness, accuracy, and generalization
• Develop and evaluate perception models leveraging multi-modal sensor data, with an emphasis on camera-based and 3D perception systems
• Collaborate with software engineers, infrastructure teams, and autonomy engineers to integrate perception models into larger production software systems
• Contribute to improvements in training pipelines, data workflows, experimentation tooling, and developer workflows that accelerate model iteration and deployment
• Participate in model architecture discussions and contribute technical recommendations within the team
• Lead small technical initiatives or model components with guidance from senior engineers
• Support and mentor Machine Learning Engineer I team members on implementation, experimentation, and machine learning best practices
• Document technical work, evaluation results, and design decisions to support knowledge sharing and long-term maintainability

Requirements:

• Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 3+ years of relevant industry experience, OR Master's degree with 1+ years of relevant experience, or equivalent practical experience
• Experience developing machine learning models for computer vision, perception, robotics, autonomous systems, or a closely related domain
• Strong programming skills in Python and PyTorch, with experience writing maintainable, production-quality machine learning code
• Experience training, evaluating, and improving deep learning models using large-scale datasets
• Experience working with image-based and/or 3D perception systems
• Solid understanding of deep learning architectures commonly used for perception applications
• Experience debugging model behavior, analyzing performance metrics, and proposing practical improvements
• Ability to independently execute complex machine learning work within well-defined problem areas
• Experience collaborating cross-functionally to integrate machine learning models into larger software systems
• Strong problem-solving skills with the ability to operate effectively in an environment with evolving technical challenges and requirements
• Experience developing perception systems for autonomous driving, robotics, or ADAS
• Experience with LiDAR, point cloud processing, sensor fusion, BEV representations, or other 3D perception techniques
• Experience with temporal perception models or video-based learning
• Experience with C++, ROS, or robotics software development
• Experience deploying machine learning models into production autonomy or robotics platforms
• Experience working with large-scale perception datasets and distributed training environments
• Familiarity with perception evaluation frameworks, model validation, and performance benchmarking
• Experience improving ML tooling, automation, training workflows, or experimentation infrastructure
• Experience leading a small technical initiative or owning a production ML component from development through deployment