The Staff Software Engineer, Autonomy Evaluation joins the Evaluation team to build and evolve the ecosystem powering autonomous driving technology. You will define strategies and architectures for metrics and analyses to evaluate software performance across the autonomy stack. Daily responsibilities include leading cross-functional efforts to embed evaluation into development workflows, inventing statistical and machine learning methods to quantify performance, and owning key KPIs for safety decisions. You will synthesize results into interactive dashboards and manage large-scale test scenario libraries. Required skills include experience with robotics or autonomous systems software, proficiency in Python and C++, and expertise in numerical and ML approaches for large-scale time series data. The role solves the technical challenge of quantifying system behavior, detecting regressions, and establishing release gating for autonomous vehicle deployment.
What does a Software Engineer earn?
Median $197400 from 2576 postings across 150 companies.
Define the strategy and architecture for metrics and analyses to evaluate autonomous driving software performance.
Lead cross-functional efforts to embed evaluation into development workflows and release decisions.
Invent and drive new statistical and ML methods to quantify performance and detect system regressions.
Own and refine key AV evaluation metrics and KPIs used for readiness and safety decisions.
Synthesize and present results and tradeoffs to stakeholders through interactive dashboards.
Develop automated workflows and analysis approaches to enable data-driven decisions across AV development.
Manage large-scale test scenario libraries and continuous evaluation pipelines.
What we're looking for
7+ years of applied experience with robotics or autonomous systems software across perception, planning, and control.
3+ years of experience leading evaluation of complex dynamic systems using numerical and ML approaches on large-scale time series data.
Proficiency in developing Python in production environments and the ability to work in large C++ autonomy codebases.
Proven cross-team technical leadership in defining strategies and influencing system and architecture decisions.
Bachelor’s, Master’s, or PhD degree in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, or a related field.
Experience in autonomous driving or high-stakes field robotics, including designing and interpreting large-scale simulation and field experiments (preferred).
Deep familiarity with statistical modeling, experimental design, and hypothesis testing, with command of Pandas, NumPy, SciPy, and visualization libraries (preferred).
Proficiency in C++, SQL, ROS, and experience with computational geometry, linear algebra, and PyTorch (preferred).
Python
C++
SQL
PyTorch
Pandas
NumPy
SciPy
ROS
Machine Learning
Data Analysis
Time-series Analysis
Statistical Modeling
Computational Geometry
Linear Algebra
Observability
Data Mining
Data Visualization