Torc Robotics · 1 week ago
Senior Machine Learning Engineer - Learned Planning/Reinforcement Learning
United States
Full-time
Remote
Senior Level
CA$226K/yr - CA$272K/yr
6+ years expTorc Robotics is a leader in autonomous driving technology, focused on developing software for automated trucks. As a Senior Machine Learning Engineer, you will design and deploy machine learning models for decision-making in autonomous trucks, collaborating with cross-functional teams to enhance model performance and reliability.
TransportationRoboticsSoftwareAutonomous Vehicles
Responsibilities
Design, develop, and deploy learned behavior models using approaches such as reinforcement learning, behavior cloning, and imitation learning
Own end-to-end model development for scoped problem areas, from data ingestion and training to evaluation and deployment
Write production-quality ML code to support scalable training, evaluation, and inference workflows
Analyze model performance, identify failure modes, and iterate to improve robustness and generalization across driving scenarios
Contribute to training pipelines, data workflows, and infrastructure, including working with large-scale datasets from simulation, fleet logs, and on-vehicle data
Collaborate with simulation, validation, and autonomy teams to test and evaluate learned behavior models across diverse environments
Support integration of learned planning models into simulation and validation frameworks, enabling faster iteration and improved coverage
Contribute to model architecture discussions and technical decision-making within the team
Mentor junior engineers on implementation, experimentation, and best practices
Qualification
Required
Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related technical field with 6+ years of industry experience, OR Master's degree with 3+ years OR PhD with 1+ years of experience
Experience applying reinforcement learning, imitation learning, or sequence modeling to robotics, autonomous systems, or complex control problems
Strong programming skills in Python and PyTorch, with experience writing production-quality ML code
Experience training, evaluating, and improving models using large-scale datasets and distributed compute environments
Solid understanding of ML architectures used in autonomy systems (e.g., transformers, RNNs, graph neural networks, policy networks)
Experience debugging model behavior, analyzing performance metrics, and improving model reliability
Ability to translate ambiguous problems into structured ML solutions and deliver results independently
Experience collaborating cross-functionally to integrate ML models into larger autonomy systems
Preferred
Experience in autonomous driving, robotics, or simulation-based training environments
Experience with reinforcement learning frameworks or distributed training systems (e.g., Ray)
Experience working with simulation environments, scenario generation, or large-scale behavior datasets
Familiarity with vehicle dynamics, motion planning, or multi-agent decision-making systems
Experience deploying ML models into production or real-world robotics systems
Experience with learned planning systems or policy learning in real-world or simulation environments
Experience integrating learned behavior models into validation and V&V workflows
Background in multi-agent modeling, driver behavior modeling, or long-horizon decision-making systems
Benefits
100% paid medical, dental, and vision premiums for full-time employees
401K plan with a 6% employer match
Flexibility in schedule and generous paid vacation (available immediately after start date)
Company-wide holiday office closures
AD+D and Life Insurance
Company
Torc Robotics
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships
501-1000 employees
H1B Sponsorship
Torc Robotics has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
94%
Represents job field similar to this job
Engineering and Development
Product Management
Customer Service and Support
Management and Executive
Creatives and Design
Marketing
Trends of Total Sponsorships
*2026 (18)
2025 (97)
2024 (41)
2023 (33)
2022 (39)
2021 (14)
2020 (7)
Funding
Current Stage
Late StageTotal Funding
unknown2019-03-29Acquired
Leadership Team
Peter Schmidt
CEO
Tobias Wessels
Chief Financial Officer
Recent News
2026-05-12
Morningstar.com
2026-05-06
Company data provided by crunchbase