Senior Machine Learning Engineer

Salary: $226,400 - 271,700 per year Requirements:

• We require a Bachelors degree plus 6+ years, a Masters degree plus 4+ years, or a PhD with 0–2 years of experience in Machine Learning, Robotics, Computer Science, or a related discipline, along with publications in leading conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, or CoRL
• We look for experience building and deploying ML models for autonomous systems, robotics, or other complex decision-making settings
• We need strong Python and PyTorch programming skills, with the ability to produce production-ready ML code
• We expect experience training and assessing models on large-scale datasets and within distributed compute environments
• We value a solid grasp of E2E ML architectures, including Transformers, BEV models, VLA/VLM approaches, or diffusion models
• We seek proven ability to troubleshoot model behavior, interpret performance metrics, and continually improve results
• We want experience shaping or influencing model architecture and training methods
• We need the ability to collaborate across functions and integrate ML systems into broader autonomy pipelines
• Preferred experience includes end-to-end or mid-to-end models for autonomous driving or robotics
• Additional pluses include experience with vision-language models, closed-loop simulation, reinforcement learning, imitation learning, distributed training frameworks such as Ray, and knowledge of vehicle dynamics, motion planning, or multi-agent systems

• We own the development and delivery of end-to-end ML models that convert multi-modal sensor inputs into driving-relevant outputs
• We train and validate models using fleet logs, simulation data, and synthetic datasets at scale
• We analyze model performance, uncover failure patterns, and lead data-driven improvements in robustness and generalization
• We design and refine training pipelines, data processes, and evaluation methods to accelerate iteration and raise model quality
• We contribute to architecture choices, including imitation learning, reinforcement learning, transformers, and vision-language-action approaches
• We work closely with Perception, Prediction, Planning, and Simulation teams to maintain alignment across the autonomy stack
• We support integration of E2E models into simulation and on-vehicle systems for closed-loop validation
• We improve tooling, experimentation practices, and reproducibility across the team
• We mentor junior engineers and help shape team best practices and technical discussions

• E2E
• Support
• Machine Learning
• PyTorch
• Python
• Robotics

More:

We are Torc, a pioneer in autonomous driving since 2007 and now part of the Daimler family, focused on software for automated trucks that will transform freight movement. We are hiring for a Senior Machine Learning Engineer - End-to-End (E2E) to build and scale learning-based systems that connect multi-modal perception to driving behavior, with a hands-on focus on execution, iteration, and delivery. We offer a collaborative, energetic, team-focused culture, a competitive compensation package with bonus and stock options, 100% paid medical, dental, and vision premiums for full-time employees, a 401K with a 6% employer match, flexible scheduling, generous paid vacation, company-wide holiday closures, and AD&D and life insurance. We are open to hiring in our Ann Arbor, MI office in a hybrid capacity or remotely within the United States, and we are committed to a diverse and inclusive workplace. We also encourage applicants to apply even if they do not meet every qualification, and our total compensation may include sign-on, relocation, and other forms of pay depending on the role.

last updated 33 week of 2026