Role: As an AI/ML Engineer on the Metrics Frameworks team, part of the Simulation, Evaluation, and Data organization, you will be an individual contributor focused on developing and optimizing infrastructure to accelerate autonomous vehicle development, testing, and deployment by creating specialized analytics frameworks and tools. We are seeking experienced software engineers to build analytical frameworks and tools that empower internal users to construct quantitative analysis pipelines and develop metrics. These metrics will support and accelerate feature design, prioritization, and development, as well as evaluate the impact of recently released features. Our analytics framework equally supports road event monitoring, data mining and training, and simulation metrics. 

About the Organization: The Simulation, Evaluation, and Data organization is dedicated to advancing the development of autonomous vehicles through cutting-edge simulation technologies. The Metrics Frameworks team within this organization focuses on creating, maintaining, and evolving the analytics framework that supports GM's goal of safe, high-performing, and scalable driverless technology. The team delivers robust and scalable tools that facilitate data-driven decision-making throughout the AV feature development lifecycle. We collaborate closely with Simulation Evaluation, Embodied AI, and System and Test Engineering teams to enhance productivity across the organization by developing automation tools and shared libraries for all engineering teams. We are accountable for the performance, reliability, and scalability OKRs of the analytics framework. This includes, but is not limited to, developing customized analytics workflows, improving operational telemetry and dashboards to track relevant KPIs for prioritization, and identifying, designing, and implementing solutions to achieve key results. 

What You’ll Do:  

• Create tooling that can receive signals from various sources (Simulation, Road, etc) and allow users to easily build quantitative analysis pipelines to extract usable insights. 

• Accelerate team’s effectiveness and efficiency by designing and implementing scalable automation tools for test creation, data collection and analysis, debugging, and performance monitoring. 

• Design and implement extensible and well-tested shared libraries that will be used by many engineers across the organization. 

• Collaborate with other frameworks and data infra teams to build and deploy tools to improve productivity. 

• Work closely with autonomous vehicle engineering to enable rapid development and model feedback. 

• Maintain a high technical standard for code quality on the team, through architectural design and code reviews. 

Your Skills & Abilities:  

• Experience developing scalable software solutions that will be used by many developers 

• Experience writing Python and C++ in a production environment (unit testing, code review, algorithm performance and tradeoffs, etc.) 

• Experience developing automation scripts (Python and Bash scripts) 

• BS in Computer Science, Electrical Engineering, Mechanical Engineering, or Aerospace Engineering 

• 5+ years of industry experience 

• Strong organizational and communication skills 

What Will Give You A Competitive Edge:  

• Experience with SQL and related tools/tech (Big Query, DuckDB, etc) 

• Experience with time-series data analysis and online performance monitoring tools 

• Experience building high performance framework / infrastructure and performance optimization in C++/Python  

• Familiarity with ROS, Pandas, Python bindings for C++, and plotting/visualization libraries 

• Familiarity with Data orchestration and transformation tools like AirTable, AirFlow, DBT, etc 

Compensation : The salary range for this role is ($118,000 and $188,400). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. 

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to the Mountain View, San Francisco, Warren or Milford Technical Center three times per week, at minimum.