Drimva

Torc Robotics

Software Engineer II, Mission Interface

$139K–$167K

Ann Arbor, MI +1 · Full-time · Posted Oct 1, 2026

Location
Ann Arbor, MI
Ann Arbor, Michigan, United States
Experience
5+ years in embedded software architecture, design, and implementation; education-linked alternatives: Bachelor’s plus 4+ years, or Master’s plus 0-3+ years. Preferred: 2–5 years of professional Python development.
Education
Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field; or Master’s Degree in those fields.

About the job

Develops production-ready software connecting autonomous truck systems with mission management and remote assistance tools, enabling vehicle guidance, status monitoring, and safe mission operations.

What you'll do

  • Design and optimize interfaces for mission planning, updates, telemetry, and vehicle status monitoring; lead real-time software development.
  • Translate system requirements into software architectures, algorithms, verification artifacts, and simulation and testing frameworks.
  • Collaborate across teams, mentor peers, and support safety-critical software quality and production releases.

What they ask for

  • Strong C++ skills (C++14/17 or later) for real-time, safety-critical, or high-performance applications.
  • Knowledge of vehicle dynamics and kinematic models.
  • 5+ years experience architecting, designing, and implementing embedded software solutions, including optimization, testing, and documentation.
  • Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus 4+ years of experience; or Master’s Degree in a related technical field plus 0-3+ years of experience.

Nice to have

  • 2–5 years of professional Python development experience.
  • Experience with robotic/autonomous frameworks (ROS/ROS2, Autoware, Apollo, etc.) and communication protocols like CAN and Ethernet.

Pay

$139,000 — $166,800 USD (total pay)

Tools

C++14/17, Python, Datadog, Tableau, Foxglove, ROS/ROS2, Autoware, Apollo

AI focus

Contribute to integrating machine learning techniques where appropriate, including route-rerouting, learned cost models, behavior prediction, and reinforcement learning for tactical decision making.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 4, 2026 (UTC)