Drimva

Motional

Senior Systems Engineer, Robotaxi Systems

$172K–$229K

Boston, Massachusetts, United States +7 · Remote · Senior · Full-time · Posted Oct 2, 2026

Location
Boston, Massachusetts, United States
Las Vegas, Nevada, United States
Pittsburgh, Pennsylvania, United States
Remote U.S.
Boston, Massachusetts, United States
Las Vegas, Nevada, United States
Pittsburgh, Pennsylvania, United States
Remote U.S.
Experience
5+ years of Systems engineering experience.
Education
Bachelor's degree in Systems Engineering, Computer Science, Aerospace Engineering, Robotics, or a related field; a Master's degree is a plus.

About the job

Designs system architectures and interfaces for robotaxi services, evaluates system performance against launch targets, and improves interactions between autonomy, remote operations, and customer-facing software.

What you'll do

  • Define architecture, requirements, and interfaces for Remote Operation, Fleet Orchestration, and Mapping systems.
  • Use data pipelines, simulation, and verification and validation campaigns to evaluate system performance and metrics.
  • Coordinate across technical and operations teams, and document system interactions and workflows.

What they ask for

  • 5+ years of Systems engineering experience.
  • Bachelor's degree in Systems Engineering, Computer Science, Aerospace Engineering, Robotics, or a related field.
  • Strong proficiency in Python; proficiency with Git and standard version control workflows.
  • Experience with complex systems interfaces, ICDs, and interface design.

Nice to have

  • Master's degree.
  • Experience with autonomous vehicle sensor data, planning or localization, simulation, V&V, performance-data tools, or HMI/UX.

Pay

$172,000 — $229,000 USD (base salary)

Tools

Python, Git, databricks, Looker, LiDAR, camera, radar, CI/CD

AI focus

Works on autonomous driving systems, including improving interactions between the Autonomy Stack, operators, and customers, and evaluating system performance. The posting also mentions machine learning techniques as a preferred qualification for performance evaluation.

Model-written summary · the original posting is authoritative

First seen Oct 27, 2026 · Last verified Nov 5, 2026 (UTC)