Torc Robotics

ML Engineer II – Learned Behaviors

Torc Robotics

full-time

Posted on:

Location Type: Remote

Location: MissouriUnited States

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Tech Stack

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 scenarios.
  • Contribute to model training pipelines and data workflows, curating behavior datasets from simulation, fleet logs, and on-vehicle data.
  • Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate learned behavior models across diverse driving environments.
  • Help integrate learned behavior models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.
  • Support the development of tooling and infrastructure that improves experimentation speed, reproducibility, and model iteration.
  • Contribute to technical discussions around model architecture and training strategies within the team.

Requirements

  • Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry experience, or a Master’s degree with 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 autonomy 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.
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 trainingmodel evaluationdata workflowsML architectures
Soft Skills
collaborationcommunicationproblem-solvinganalytical skillstechnical discussion
Certifications
Bachelor’s degreeMaster’s degree