Machine Learning Engineer II
Torc Robotics
full-time
Posted on:
Location Type: Remote
Location: Missouri • United States
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About the role
- Develop and train machine learning models for learned behavior systems, including approaches such as behavior cloning, imitation learning, and reinforcement learning.
- Implement production-quality ML code to support model training, evaluation, and inference within the autonomy stack.
- Analyze model performance, identify failure modes, and propose improvements to increase robustness and generalization across different scenarios.
- Contribute to model training pipelines and data workflows, organizing behavior datasets from simulation, fleet logs, and vehicle data.
- Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across various driving environments.
- Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.
- Support the development of tools and infrastructure that improve experiment velocity, reproducibility, and model iteration.
- Contribute to technical discussions regarding model architectures and training strategies within the team.
Requirements
- Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or another related technical field with at least 4 years of industry experience, or a Master’s degree with at least 2 years of experience.
- Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling to robotics, autonomous systems, or complex control environments.
- Strong programming skills in Python and PyTorch, with experience writing production-quality ML code.
- Experience training and evaluating machine learning models using large datasets and scalable compute environments.
- Understanding of ML architectures used in autonomous driving systems, such as transformers, graph neural networks, or sequence models.
- Experience debugging model behavior, analyzing performance metrics, and iterating on training pipelines.
- Ability to collaborate with cross-functional teams to integrate ML models into larger software systems.
Benefits
- A competitive compensation package including bonuses and stock option grants
- Medical, dental, and vision coverage for full-time employees
- A retirement savings plan (RRSP) with a 4% employer contribution
- A public transit subsidy (Montreal area only)
- Flexible scheduling and generous paid time off
- Company-wide office closures during major holidays
- Life insurance
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningbehavior cloningimitation learningreinforcement learningPythonPyTorchmodel evaluationdata workflowsmodel architecturesdebugging
Soft Skills
collaborationcommunicationproblem-solvinganalytical thinkingtechnical discussion