Senior, Machine Learning Engineer - 3D Perception

Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. As a Senior Machine Learning Engineer – 3D Perception, you will advance perception capabilities by developing machine learning solutions that enhance environmental understanding and system performance.

Responsibilities:

• Design, develop, and deploy production machine learning models supporting Torc's perception systems
• Own end-to-end model development for scoped perception problem areas, from data preparation and training through evaluation and deployment
• Write production-quality ML code to support scalable training, evaluation, and inference workflows
• Analyze model performance, identify failure modes, and iterate to improve robustness, accuracy, and generalization across diverse driving environments
• Develop and optimize 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 production autonomy software
• Support improvements to training pipelines, data workflows, and tooling that accelerate model iteration and deployment
• Contribute to model architecture discussions and technical decision-making within the team
• Mentor junior engineers on implementation, experimentation, and machine learning best practices

Requirements:

• Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 6+ years of industry experience, OR Master's degree with 3+ years, OR Ph.D. with 1+ years of experience
• Experience developing production machine learning models for computer vision, perception, robotics, or autonomous systems
• Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
• Experience training, evaluating, and improving deep learning models using large-scale datasets
• Experience working with image-based and/or 3D perception systems
• Strong understanding of deep learning architectures commonly used for perception applications
• Experience debugging model behavior, analyzing performance metrics, and improving model reliability
• Ability to translate ambiguous perception challenges into practical machine learning solutions and deliver results independently
• Experience collaborating cross-functionally to integrate ML models into larger software systems
• Experience developing perception systems for autonomous driving or robotics
• Experience with LiDAR, point cloud processing, sensor fusion, 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, infrastructure, or developer workflows to accelerate model iteration