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Torc Robotics

Autonomous truck software for Level 4

Machine Learning Engineer - II, 3D Perception

Computer VisionConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • A bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of relevant industry experience, or a master's degree with 3+ 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 and the ability to operate effectively amid evolving technical challenges and requirements.

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.

Desired Qualifications

  • Experience developing perception systems for autonomous driving, robotics, or advanced driver-assistance systems.
  • Experience with LiDAR, point cloud processing, sensor fusion, bird's-eye-view representations, or other 3D perception techniques.
  • Experience with temporal perception models or video-based learning.
  • Experience with C++, Robot Operating System (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 machine learning tooling, automation, training workflows, or experimentation infrastructure.
  • Experience leading a small technical initiative or owning a production machine learning component from development through deployment.

About the Company

Torc Robotics

Autonomous truck software for Level 4

Torc Robotics builds software for autonomous trucks, aiming to enable Level 4 self-driving capabilities for freight transport. They develop driving systems that let heavy trucks operate autonomously under certain conditions, and they work with truck manufacturers and fleet operators to bring these solutions to market. The company integrates sensors from partners (such as Luminar Technologies) and provides ongoing updates and support to ensure reliability and performance. Unlike more general AV players, Torc focuses on commercial trucking and leverages strategic partnerships (for example with Daimler Trucks) to integrate its software into production vehicles and fleets. Its goal is to improve road safety and freight efficiency by deploying scalable, commercial autonomous trucking solutions.

Company size
501-1,000
Company stage
M&A
Total funding
Not listed
Headquarters
Blacksburg, VA
Founded
2005

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