The Senior Software Engineer, Autonomy Evaluation joins the Evaluation team to build and evolve the ecosystem powering autonomous driving technology. You will architect and implement metrics and analyses to introspect software performance across the autonomy stack, specifically focusing on perception, prediction, and planning models. Day-to-day responsibilities include designing algorithms to aggregate metrics from simulations and on-road runs, developing statistical and ML methods to quantify system behavior, and maintaining interactive dashboards for trend analysis and drift detection. You will utilize Python, Pandas, NumPy, SciPy, and C++ to process large-scale time-series data. The role involves solving complex problems in autonomous vehicle quality by creating continuous evaluation pipelines, risk assessment components, and leveraging vision-language models to classify performance and prioritize validation efforts across diverse operational domains.
What does a Software Engineer earn?
Median $197400 from 2576 postings across 150 companies.
Architect and implement metrics to monitor autonomous driving software performance across the autonomy stack.
Design and implement algorithms to summarize, aggregate, and cluster metrics from simulations and on-road runs.
Develop statistical and ML methods to quantify system behavior and identify performance patterns across diverse scenes.
Build and maintain interactive dashboards and reports to provide explainable insights on trend analysis and drift detection.
Leverage vision-language models and large language models to classify performance and prioritize validation efforts.
Maintain high technical standards through system design, code reviews, testing, and adherence to software engineering best practices.
Interface with cross-organizational partners to articulate requirements and share best practices regarding experiment design.
What we're looking for
5+ years of applied experience with robotics or autonomous systems software, data analysis, ML evaluation, or autonomy analytics.
3+ years of experience evaluating dynamic systems using numerical and/or ML approaches, including time-series data and interconnected subsystems.
Strong proficiency in developing Python in production environments, including testing, performance, and code review.
Proficiency with Pandas, NumPy, SciPy, and plotting/visualization libraries for large-scale data analysis and reporting.
Comfort working with C++ codebases, including reading, debugging, and instrumenting core algorithms.
Demonstrated technical leadership in driving architectural decisions, influencing cross-team designs, and owning complex features end-to-end.
Bachelor’s, Master’s, or PhD in Computer Science, Robotics, Mechanical or Aerospace Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience.
Experience in autonomous driving or field robotics, including visualizing and interpreting results from simulation and field experiments (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