Senior Robotics Engineer

Motional•Boston, MA

7d•$149,000 - $198,500

About The Position

Motional is seeking a Senior Robotics Engineer for its Systems Readiness and Performance team. The team connects software development with real-world deployment by driving system design, verifying and validating the autonomy stack, and defining, measuring, and validating system performance targets. It works with autonomy, infrastructure, and operations stakeholders to support the safety case for commercial launch of driverless IONIQ 5 robotaxis in Las Vegas. The engineer will investigate and diagnose complex autonomous vehicle behaviors across on-road, resimulation, and synthetic simulation environments. This role owns ambiguous investigations end to end, using Python, custom Spaceship tooling, and data visualization platforms to identify root causes across the autonomy stack. The work supports development of safe and reliable autonomous technology by turning technical investigations and performance data into clear findings for engineering teams, release narratives, and executive reporting. The position calls for a professional with at least five years of software or systems engineering experience on safety-critical, complex systems and a thorough understanding of robotics systems. A bachelor's degree in a relevant engineering discipline or equivalent work experience is required; a master's degree is a strong plus. The role's estimated base salary range is $149,000–$198,500 USD. Additional compensation may include a bonus or company equity. Eligible candidates may participate in Motional's benefits program.

Requirements

Bachelor's degree in Engineering, such as Computer Science, Electrical, Systems, or Robotics, or equivalent work experience.
At least 5 years of professional software or systems engineering experience working on safety-critical, complex systems such as autonomous vehicles, robotics, medical devices, or aerospace.
Thorough understanding of robotics systems, including sensors, actuators, and software autonomy stacks.
Strong proficiency in Python for data analysis and scripting, with a strong understanding of modern software development principles.
Experience building data visualizations using Python frameworks.
Strong analytical and problem-solving skills for complex system performance evaluation.
Ability to reason logically, remove bias, perform root-cause analysis using system logs, and maintain rigorous data quality and testing.
Proficiency with Git and standard version control workflows.
Comfort working in a fast-paced, agile CI/CD environment.
Ability to work independently and effectively with a multidisciplinary team.
Excellent communication skills, including the ability to synthesize complex technical findings into clear summaries for cross-functional teams and executive leadership.

Nice To Haves

Master's degree.
Experience with AV-specific diagnostic and visualization tools, such as Planner Analyzer, for troubleshooting complex autonomy behaviors.
Knowledge of statistical analysis and machine learning techniques relevant to performance evaluation.
Willingness to learn Business Intelligence tools such as Looker.

Responsibilities

Investigate undesirable autonomous vehicle behaviors across simulation, hardware-in-the-loop (HIL), and on-road operations.
Own complex investigations from initial triage through resolution, working autonomously with little to no oversight.
Debug behaviors across perception, prediction, localization, planning, controls, and vehicle systems, including emergent behaviors caused by interactions between subsystems.
Analyze system logs, telemetry, and software outputs using Python.
Develop automated diagnostic workflows and internal tools using Python and Spaceship to accelerate and scale investigations.
Build interactive dashboards using Python frameworks and Business Intelligence tools to measure, analyze, and report on AV system performance.
Develop and systematically test technical hypotheses based on incomplete or ambiguous evidence, distinguishing symptoms from underlying causes.
Identify recurring undesirable behaviors, regressions, and emerging system-level performance issues, and categorize them into meaningful failure modes.
Synthesize technical findings and performance metrics into clear summaries for executive reporting, release narratives, and cross-functional communication.
Deliver accurate root-cause diagnoses and actionable engineering resolutions, robust diagnostic automation, and useful visualizations and insights.