Developing software for automated trucks to transform how the world moves freight at Torc, a part of the Daimler family
Requirements
- 10+ years of professional experience (or equivalent) in applied machine learning in autonomous vehicles, robotics, simulation or a related domain
- M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field (or equivalent practical experience)
- Proven track record of designing and shipping learned behavior or policy models (e.g., behavior cloning, imitation learning, RL, multi-agent models) in production or near-production systems
- Strong programming skills in the AI domain(Python, Pytorch (Lightning), pandas )
- Experience with open-source distributed computing framework, specifically Ray
- Deep understanding of ML architectures (e.g., RNNs, transformers, graph neural networks, behavior prediction networks) and system-level integration into autonomy stacks
Responsibilities
- Lead architecture, development, and validation of learned behavior models (e.g., driver mimicry, multi-agent interaction, behavior cloning, reinforcement learning) for highway and freight-truck autonomy
- Define and implement data strategies: collect, label, and curate large behavior datasets (in-vehicle, simulation, fleet logs) for training and evaluation
- Develop scalable model training pipelines, infrastructure, and tooling to iterate quickly on behavior models, from prototype to production deployment
- Design and track performance metrics, analyze model behavior, diagnose failure modes, and drive continuous improvement of learned behaviors in simulation and on-vehicle
- Work with simulation, scenario, and validation teams to embed learned behavior models into verification and validation frameworks, ensuring coverage across operational design domains (ODDs)
- Mentor and lead mid and senior-level ML engineers, set technical direction, and drive best practices in learned behavior engineering across the team
Other
- M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or related field (or equivalent practical experience)
- 10+ years of professional experience (or equivalent) in applied machine learning in autonomous vehicles, robotics, simulation or a related domain
- 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)
