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Mid LevelFull-timePythonRustC++ML
Salary Range
$35,700 - $48,300 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a passionate Software Engineer to join our Waymo Commercialization team and help build the systems that improve Waymo's core ride-hailing and fleet management systems. This role involves working on cross-cutting problems that require cross-team collaboration to develop and deliver business-critical infrastructure.
Key Responsibilities
- →Design and operate high-performance, low-latency data pipelines for both massive-scale simulation and real-world monitoring.
- →Improve the signal quality of driving tests by ensuring simulation results are highly predictive of real-world behavior and implementing metrics to measure simulation accuracy.
- →Deploy and potentially contribute to ML models that identify "interesting" driving scenarios, optimizing the efficiency of testing through robust integrations with large-scale models.
- →Champion code health and developer experience by applying best practices to the simulation and monitoring ecosystems.
- →Partner with Data Scientists and Systems Engineers to translate complex vehicle telemetry into actionable insights regarding the Waymo Driver’s internal logic.
Requirements
- ✓5+ years of full-time software engineering experience, or a quantitative PhD with 2+ years of professional software engineering experience
- ✓Proficiency in C++ (or another OOP language)
- ✓Familiarity with Python and SQL
- ✓Excited about autonomous driving, Simulation + Eval
- ✓We prefer
- ✓7+ years of industry experience or 3+ years post-doc experience in a quantitative- or quality-focused engineering role
- ✓Experience as a technical lead for a team, performing tasks like developing hypotheses, designing and running experiments, processing data from experiments, synthesizing conclusions, and ensuring the long-term stability and health of the production system
- ✓B.Sc., M.Sc., or PhD in Computer Science
- ✓Experience working with large FAANG-scale distributed systems.
