Senior Autonomy Evaluation Engineer

General Motors; Austin (TX); On-site; USD 185,000 - 284,000; Full time

Benefits offered by this job

Health benefits

Company vehicle program

Relocation benefits

Job summary

General Motors seeks a senior specialist to define metrics and evaluation methods for autonomous driving software across the stack.

You will lead cross-functional teams with autonomy, systems, simulation, and data groups to integrate evaluation into development and release decisions. Expect to advance ML/statistical approaches, quantify performance, and present insights with dashboards.

Qualifications

• 7+ years of applied experience with robotics or autonomous systems software across perception to planning and control.
• 3+ years leading evaluation of complex dynamic systems using numerical and ML approaches on large-scale time series data.
• Production-level Python in team environments; strong C++ experience in large autonomy codebases.
• Proven cross-team technical leadership and ability to influence system/architecture decisions.
• PhD, Masters, or Bachelor’s degree in CS, Robotics, Mechanical or Aerospace Engineering, ML, or related field.

Responsibilities

• Define strategy and architecture for metrics to evaluate autonomous driving software performance across the stack.
• Lead cross-functional efforts with autonomy, systems, simulation, and data teams to embed evaluation into development workflows.
• Invent and drive statistical and ML methods to quantify performance, detect regressions, and reveal patterns at scale.
• Own key AV evaluation metrics and KPIs; synthesize results for stakeholders and enable dashboards.

Skills

Robotics software

Autonomous systems

Python production

C++ codebase

Cross-team leadership

Education

CS/Robotics/Engineering/ML degrees

Tools

ROS

SQL

Pandas

NumPy

SciPy

PyTorch

Job description

General Motors seeks a senior specialist to define metrics and evaluation methods for autonomous driving software across the stack.

You will lead cross-functional teams with autonomy, systems, simulation, and data groups to integrate evaluation into development and release decisions. Expect to advance ML/statistical approaches, quantify performance, and present insights with dashboards.