ML Engineer II – End to End

Torc Robotics

full-time

Posted on: 3/19/2026

Location Type: Remote

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About the role

Develop and train machine learning models for End-to-End perception and planning, including approaches such as 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 datasets from simulation, fleet logs, and on-vehicle data.
Collaborate with simulation, validation, and autonomy engineering teams to test and evaluate End-to-End models across diverse driving environments.
Help integrate End-to-End models into simulation and testing workflows, enabling faster iteration and more comprehensive validation.
Support the development of tooling and infrastructure that improve experimentation speed, reproducibility, and model iteration.
Contribute to technical discussions around model architecture and training strategies within the team.

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 computer vision, imitation learning, or reinforcement learning, 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 End-to-End systems, such as BEV models, Transformers, VLA, or diffusion 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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningimitation learningreinforcement learningcomputer visionPythonPyTorchmodel trainingmodel evaluationML architecturesdebugging

Soft Skills

collaborationcommunicationproblem-solvinganalytical thinkingtechnical discussion

Certifications

Bachelor’s degreeMaster’s degree