Autonomy Evaluation Engineer: Metrics & Dashboards

General Motors; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

General Motors is seeking a senior AV analytics professional to drive evaluation platforms for autonomous driving systems. You will design metrics, implement analyses, and build dashboards that translate complex telemetry into actionable insights for engineers and leadership.

You will lead cross-team collaborations, apply ML methods to detect performance patterns, and help advance scalable validation and release decisions across simulation and field data.

Qualifications

• 5+ years in robotics/autonomy software, data analysis, or ML evaluation.
• Experience evaluating dynamic systems and time-series data.
• Proficiency in Python in production environments with testing and reviews.
• comfortable with C++ codebases and debugging.
• Strong leadership and cross-team influence.

Responsibilities

• Architect metrics and analyses for autonomous driving performance across the autonomy stack.
• Develop analysis algorithms to summarize and cluster metrics from simulations and on-road data.
• Advance statistical/ML methods to quantify performance and detect patterns.
• Evaluate ML components and perception/prediction/planning models.
• Build dashboards and reports with clear insights for stakeholders.
• Leverage VLMs/LLMs for classification of autonomy performance and scenario prioritization.
• Maintain high technical standards via design reviews, testing, and observability.
• Collaborate with cross-organizational partners to share best practices in evaluation.

Skills

Robotics

Python

Pandas/NumPy

C++

ML evaluation

Leadership

Data visualization

Education

CS/Robotics/ML degree

Tools

ROS

SQL

Logging pipelines

PyTorch

Job description

General Motors is seeking a senior AV analytics professional to drive evaluation platforms for autonomous driving systems. You will design metrics, implement analyses, and build dashboards that translate complex telemetry into actionable insights for engineers and leadership.

You will lead cross-team collaborations, apply ML methods to detect performance patterns, and help advance scalable validation and release decisions across simulation and field data.