Senior AI-Driven Autonomy Evaluation Engineer

General Motors; Sunnyvale (CA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Total Rewards resources

Accommodations

Job summary

General Motors in Sunnyvale is seeking a highly experienced autonomy evaluation engineer to design metrics, analyses, and dashboards across the autonomy stack, collaborating with cross-functional teams.

You will develop ML evaluation methods, validate perception/prediction/planning models, and help drive data-driven decisions for scalable AV deployment.

Responsibilities include building dashboards, applying VLM/LLM where appropriate, and upholding software engineering standards.

Qualifications

• 5+ years of robotics or autonomous systems software experience.
• 3+ years evaluating dynamic systems with time-series data.
• Strong Python production experience, testing and code reviews.
• Proficiency with Pandas, NumPy, SciPy and visualization libraries.
• C++ reading, debugging, and instrumenting core algorithms.
• Proven leadership and cross-team influence.
• Advanced degree or equivalent practical experience in related fields.

Responsibilities

• Architect and implement metrics and analyses for autonomy performance across the stack.
• Design analysis algorithms for simulations and on-road data.
• Develop new statistical and ML methods to quantify performance.
• Evaluate ML components including perception, prediction, and planning.
• Build and maintain autonomy evaluation dashboards and reports.
• Collaborate with cross-organizational partners to share requirements and best practices.
• Adhere to software engineering standards, testing, and observability.

Skills

Robotics experience

Python production experience

C++ proficiency

Data analysis

Leadership

Communication

Education

Bachelor's/Master's/PhD in CS/Robotics or related field

Tools

Python

Pandas

NumPy

SciPy

ROS

SQL

PyTorch

Job description

General Motors in Sunnyvale is seeking a highly experienced autonomy evaluation engineer to design metrics, analyses, and dashboards across the autonomy stack, collaborating with cross-functional teams.

You will develop ML evaluation methods, validate perception/prediction/planning models, and help drive data-driven decisions for scalable AV deployment.

Responsibilities include building dashboards, applying VLM/LLM where appropriate, and upholding software engineering standards.