About the Company

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Meet the Team

As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will support the day-to-day operations that keep Torc's model development ecosystem running smoothly. Our team is comprised of engineers with deep expertise in ML and RL frameworks, embedded systems, and autonomous driving — united by a focus on getting models from development into the real world reliably and at scale.

In this role, you will provide general MLOps support to model development teams, helping triage issues, maintain pipelines, and ensure engineers have what they need to move fast. You'll gain broad exposure across the ML stack and grow alongside a team working on some of the most complex model infrastructure in autonomous trucking.

What You’ll Do

• Provide on-call MLOps support for model development teams, triaging and resolving pipeline issues as they arise.
• Assist in debugging model development workflows and identifying root causes across the ML stack.
• Collaborate with senior engineers to improve tooling, documentation, and operational processes.
• Communicate and collaborate with model development teams and broader stakeholders, ensuring issues are resolved quickly and findings are shared across the organization.

What You’ll Need to Succeed

• Bachelor's Degree in Computer Science, Electrical Engineering, Robotics, or related field plus 1+ years of relevant experience; or equivalent practical experience.
• Proficiency in Python, with foundational experience in ML frameworks such as PyTorch and familiarity with model training pipelines.
• Experience with MLOps tooling — CI/CD systems, monitoring, logging, and pipeline orchestration.
• Strong debugging and problem-solving skills with an ability to triage issues under pressure.
• Clear communicator who can work across teams and translate technical issues for different audiences.

Bonus Points