Staff Software Engineer, Autonomy Evaluation

Accountabilities: • Define the technical strategy and architecture for metrics, analyses, and evaluation systems that measure autonomous driving software performance across the autonomy stack.

• Lead cross-functional technical initiatives with autonomy, systems engineering, simulation, and data teams to integrate evaluation into development workflows and release decisions.

• Develop and apply new statistical, machine learning, and ML introspection methods to quantify system performance, detect regressions, and identify behavioral patterns at scale.

• Own and continuously refine key autonomous vehicle evaluation metrics and KPIs used to support readiness, safety, and release decisions.

• Analyze large-scale time-series and experimental datasets to generate meaningful system-level insights and identify areas for improvement.

• Synthesize complex evaluation results, tradeoffs, and recommendations for technical and cross-functional stakeholders.

• Build or enable interactive dashboards and analytical tools that make evaluation insights readily accessible to partner teams.

• Provide technical leadership across multiple teams, influencing system architecture, evaluation strategies, and engineering decisions.

• Help evolve large-scale evaluation platforms, scenario libraries, continuous evaluation workflows, and risk assessment processes supporting autonomous systems development.

Requirements

• 7+ years of applied experience developing robotics or autonomous systems software, with experience spanning multiple subsystems from perception through planning and vehicle control.

• 3+ years of experience leading evaluation of complex dynamic systems using numerical and machine learning approaches on large-scale time-series data.

• Strong production Python development experience in collaborative engineering environments.

• Ability to work effectively within large C++ autonomy codebases.

• Proven cross-team technical leadership, including defining strategies adopted by multiple teams and influencing system and architecture decisions.

• Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Mechanical Engineering, Aerospace Engineering, Machine Learning, or a related technical field.

• Experience with autonomous driving or high-stakes field robotics, including designing, executing, and interpreting large-scale simulation and field experiments, is preferred.

• Deep knowledge of statistical modeling, experimental design, and hypothesis testing for autonomy evaluation.

• Strong experience with Pandas, NumPy, SciPy, and data visualization libraries.

• Proficiency in C++ and SQL, with experience shaping logging systems, data schemas, and evaluation pipelines for large-scale autonomy testing.

• Experience with ROS or other inter-process communication frameworks, robotics-stack logging, and large-scale experiment databases is preferred.

• Experience designing or scaling evaluation platforms and working with computational geometry, linear algebra, PyTorch, and machine learning is a plus.

• Background in modeling agent interactions and designing or owning release-gating criteria and processes for autonomous systems is preferred.

• Strong communication, collaboration, and problem-solving skills, with the ability to influence technical decisions across organizational boundaries.

Benefits

• Remote/Hybrid work arrangement with a Remote - United States location option.

• Full-time employment.

• Opportunity to work on advanced autonomous driving technology with direct impact on safety, system quality, and deployment readiness.

• Work alongside multidisciplinary teams spanning autonomy, simulation, systems engineering, data, and safety.

• Access to comprehensive total rewards and employee benefits designed to support well-being at work and at home.

• Benefits and programs supporting physical, financial, and emotional well-being.

• Opportunities for professional development and career growth within a global technology and engineering organization.

• Inclusive workplace culture focused on belonging, collaboration, innovation, and meaningful impact.

• Reasonable accommodations are available for qualified individuals with disabilities throughout the employment and application process.

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