Senior Autonomy Evaluation Engineer

General Motors; Denver (CO); On-site; USD 140,000 - 210,000; Full time

Job summary

General Motors is seeking a seasoned autonomy analytics engineer to advance evaluation across perception, prediction, and planning components. You will implement metrics, run analyses on simulation and on-road data, and develop ML methods to identify patterns in complex scenes.

Collaboration with robotics and software teams is essential. The role requires deep Python experience in production settings, strong knowledge of Pandas/NumPy/SciPy, and proficiency in C++ and ROS.

Qualifications

• 5+ years of robotics or autonomous systems software experience.
• 3+ years evaluating dynamic systems using time-series data and ML approaches.
• Strong proficiency developing Python in production environments.
• Proficiency with Pandas, NumPy, SciPy, and plotting/visualization libraries for large-scale data analysis.
• Comfort working with C++ codebases, including reading, debugging, and instrumenting core algorithms.
• Strong curiosity to question anomalous data and root-cause discrepancies.
• Demonstrated technical leadership and ownership of complex features or services end-to-end.
• Bachelor’s, Master’s, or PhD in CS, Robotics, Mechanical/Aerospace Eng, ML, Data Science, or related field, or equivalent practical experience.

Responsibilities

• Architect and implement metrics to introspect autonomy software performance across the stack.
• Design and implement analysis algorithms to summarize, aggregate, and cluster metrics from simulations and on-road runs.
• Propose and develop ML methods to quantify performance and identify patterns across diverse scenes.
• Develop methods to introspect ML components, including evaluation of perception, prediction, and planning models.
• Build and maintain autonomy evaluation dashboards and interactive reports for insights.

Job description

General Motors is seeking a seasoned autonomy analytics engineer to advance evaluation across perception, prediction, and planning components. You will implement metrics, run analyses on simulation and on-road data, and develop ML methods to identify patterns in complex scenes.

Collaboration with robotics and software teams is essential. The role requires deep Python experience in production settings, strong knowledge of Pandas/NumPy/SciPy, and proficiency in C++ and ROS.