ML Engineer II: Learned Behaviors & RL

Torc Robotics; United States; Hybrid; USD 153,000 - 184,000; Full time

Benefits offered by this job

Stock options

Medical, dental, vision premiums paid

401K with 6% employer match

Flexible schedule

Paid vacation

AD&D and Life Insurance

Job summary

Torc Robotics is seeking a Machine Learning Engineer II – Learned Behaviors to develop and deploy learned behavior models powering autonomous trucks. You will build and validate ML models, curate data from simulation and field logs, and collaborate with perception, prediction, planning, and safety teams.

You’ll implement production-grade ML code, analyze performance, and help scale training pipelines for robust, real-world operation. Hybrid or remote US work options are available.

Qualifications

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with 4+ years of industry 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.

Responsibilities

• 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.

Skills

Python

PyTorch

Imitation learning

Reinforcement learning

Sequence modeling

Transformers

Graph neural networks

Debugging ML models

Cross-functional collaboration

Production ML code

Education

Bachelor's degree in CS/Robotics/EE/ML (4+ years)

Master's degree in ML/related (2+ years)

Tools

Ray

Job description

Torc Robotics is seeking a Machine Learning Engineer II – Learned Behaviors to develop and deploy learned behavior models powering autonomous trucks. You will build and validate ML models, curate data from simulation and field logs, and collaborate with perception, prediction, planning, and safety teams.

You’ll implement production-grade ML code, analyze performance, and help scale training pipelines for robust, real-world operation. Hybrid or remote US work options are available.