Staff Software Engineer, Cruise

• A Masters or PhD degree or equivalent experience in Robotics, Transportation, Physics, Aerospace Engineering, or other relevant industry experience
• 5+ years post-academic experience in evaluating large models, data science, machine learning, or a closely-related field
• Strong software engineering foundation and proficiency in production-environment coding and best practices
• Proficiency in SQL and Python
• Experience designing, training, and critically analyzing machine learning models for big data
• Solid statistical foundations, familiarity with hypothesis testing, statistical power, and common biases in data
• Experience designing, developing and maintaining automated reporting tools for management and other partners
• Creative, inventive, and passionate about seeking new solutions to problems and opportunities
• A track record of leading multi-functional initiatives and collaborating with engineering and product teams
• 3+ years of experience mentoring other data scientists

Desirable

• As a Staff Autonomy Evaluation Engineer, you drive impact-focused projects that address the everyday challenges that our AV's face on urban roads- ones that do not have standard solutions available
• Our team leverages domain knowledge and the ability to answer questions with data, focusing on evaluating the entire autonomous vehicle (AV) stack
• This gives team members a unique opportunity to deeply understand the stack and solve complex, undefined problems in a rapidly evolving domain
• Defining success criteria from ambiguous problem statements
• Driving evaluation strategies and roadmaps, leading the development, monitoring and analysis of safety, roadcraft and compliance metrics for core autonomous capabilities
• Ensuring comprehensive validation of AV performance with high fidelity signals
• Streamlining testing and road monitoring process in collaboration with AV Engineers to build a fast feedback loop to AV model development
• Mentoring fellow Data Scientists and fostering a positive, collaborative work environment
• Role-modeling a positive, humble and growth-oriented attitude
• Building high quality data miners and metrics that serves testing, road monitoring, and model training
• Analyzing AV performance data to extract insights and opportunities for optimization
• Developing new methodologies, e.g., machine learning based approaches, to scalably improve the quality of metrics
• Test and deploy and your methods in our simulation environment
• Collaborating with AV Software Engineers, Systems Engineers, Test Engineers along with Product Management and other stakeholders to build shareable tools, methods, and dashboards
• Converting insights into actionable recommendations for AV software development and launch readiness decisions, and succinctly communicate these findings to partners and leadership