Staff Software Engineer - Behaviors

Company: TORC Robotics

Location: Fort Worth, TX (Remote)

Salary: $186,200 - $223,400 a year

Type: Full-time

Remote: Yes

Posted: 2026-06-06

About this role

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:

Join Torc's Behaviors Team, where we develop the planning, prediction, and decision-making systems that determine how our autonomous trucks navigate the world safely, efficiently, and predictably. Our team operates at the intersection of robotics, machine learning, optimization, simulation, and safety, building the core autonomy capabilities that translate perception into action.

We are seeking a Staff Software Engineer who thrives in a hands-on technical leadership role and is passionate about solving some of the most challenging problems in autonomous driving. This position combines deep technical ownership with cross-functional influence, requiring expertise in motion planning, behavior prediction, autonomy architecture, and production software development. You will help shape the future direction of Torc's planning systems while mentoring engineers and driving execution across critical autonomy initiatives.

What You'll Do

  • Design, develop, and maintain core planning and prediction systems, including trajectory generation, behavior prediction, decision-making, and motion planning algorithms for autonomous trucks.
  • Advance and evaluate multiple planning approaches, including optimization-based, learning-based, and hybrid architectures, making data-driven decisions on where each methodology delivers the greatest value.
  • Own technic...

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