Torc Robotics logo
Torc Robotics
Posted 54 days agoVerified live 1d ago

Machine Learning Engineer, II - 3D Perception

Brief overview

Remote
UndergradOr in progress
1+ yrsMinimum
158 H-1B approvalsDept. of Labor
40 green cardsCertified filings
PythonPyTorchMachine LearningComputer VisionDeep Learning3D PerceptionImage-Based PerceptionLarge-Scale Dataset TrainingModel EvaluationLiDARPoint Cloud ProcessingSensor Fusion

About the company

Torc Robotics logo
Torc Roboticstorc.ai

A leader in autonomous driving focused on developing software for automated trucks.

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
158H-1B approved
99%approval rate
38new H-1B hires
40PERM certified
$167,254median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
202332
202438
202567
202621
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202311
20249
20258
20266
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20236
202424
202510
Top sponsored roles
Software Engineer 2Senior Software EngineerEngineering ManagerSoftware Engineer IISenior Machine Learning Engineer
Sponsored employees from
IndiaChinaSouth KoreaKazakhstanNepal

Job description

Summary

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

Skills

  • 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

Qualifications

Must Haves

  • 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

Nice to Haves

  • 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

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
  • Generous paid vacation available immediately after start date
  • Company-wide holiday office closures
  • AD+D and Life Insurance
  • Hybrid work capacity in Ann Arbor, MI, Blacksburg, VA, and Fort Worth, TX
  • Remote work in the United States
  • Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package

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