Software Engineer - Behaviors & Planning

Overland AI•Seattle, WA

1d•Onsite

About The Position

Overland AI is seeking a Software Engineer to join the team responsible for determining where autonomous ground vehicles go and how they get there in off-road terrain with degraded GPS and intermittent communications. The engineer will work alongside planning, optimization, and systems engineers, ship code to vehicles early, and grow toward co-owning a core part of the stack within the first 6–12 months. Strong fundamentals, curiosity, and ownership are emphasized; extensive production experience is not required. The role may focus on systems (planning-stack architecture, performance, tooling, and reliability), planning (navigation and decision-making under uncertainty using learned and classical methods), or trajectory optimization (MPC/MPPI, vehicle modeling, and real-time optimization), matched to the candidate's interests and team needs. The position is onsite in Seattle, Washington.

Requirements

BS or MS in Computer Science, Robotics, Engineering, or a related field, or equivalent experience; PhD graduates are welcome.
1–3 years of professional experience; internships, research, and substantial projects count.
Solid programming aptitude in C++ or Python and a desire to become excellent in both.
Strong computer science fundamentals, including data structures, algorithms, and complexity.
Enthusiasm for supporting periodic field testing.

Nice To Haves

PhD in a relevant field.
Experience with both learned planning approaches (such as learned costmaps, imitation learning, or reinforcement learning) and classical approaches (such as search, sampling, or optimization).
Experience integrating prior or opportunistic map data with onboard perception.
Off-road UGV and/or on-road AV planning experience; UGV experience is a plus, not a requirement.
Experience in DDIL environments.

Responsibilities

Implement, test, and improve features in the behaviors and planning stack using C++ and Python in a shared codebase.
Use off-road driving data to evaluate changes and identify regressions.
Debug issues using logs, simulation, and field data, with mentorship.
Participate in field tests and observe code running on vehicles.
Participate in design discussions and code reviews, giving and receiving feedback.