Staff Software Engineer

Summary

Join Stack, a company developing revolutionary AI and autonomous systems for the trucking industry, as a Staff Software Engineer. Contribute to the development of the Trajectory Selection system, a crucial part of our motion planning stack. You will work on robotics, real-time systems, and decision-making algorithms to ensure safe and efficient autonomous navigation. Collaborate with cross-functional teams, including Planning, Perception, Controls, and Simulation. Design and implement high-performance software balancing safety, comfort, and efficiency. We seek strong software engineers with motion planning experience to develop and deploy motion planning components for next-generation self-driving systems. A mission-driven mindset and customer-centric approach are essential.

Requirements

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, or related field
• 5+ years of experience in software engineering, with at least 3+ in robotics, motion planning, or autonomous systems
• Proficiency in C++ (C++14/17), with solid software design and debugging skills
• Deep understanding of trajectory generation and evaluation in dynamic environments
• Experience with numerical optimization, search/planning algorithms (e.g., A*, RRT), or control theory
• Strong understanding of kinematic/dynamic models and constraints in vehicle or robotic systems

Responsibilities

• Design and implement the trajectory selection module for real-time motion planning
• Develop algorithms to evaluate and score candidate trajectories based on safety, kinematics, comfort, and goal achievement
• Integrate cost models, constraints, and prediction outputs from upstream systems (e.g., perception, forecasting)
• Optimize system performance for runtime efficiency and determinism in safety-critical applications
• Collaborate with other domain experts (e.g., ML, prediction, controls) to ensure seamless system integration
• Write clean, well-documented, and tested code in C++ and Python

Preferred Qualifications

Experience with ML models is a plus