Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.
Simulation is key to ensuring the safety of autonomous vehicles at Zoox. In this critical role, you will ensure Zoox’s simulation framework is a trustable platform for AI driving software validation, by analyzing the accuracy and realism of the simulator, and how effective the sim platform is at predicting real-world driving performance. You will work cross-functionally with our AI/autonomy teams, systems engineering and safety analysis teams, QA teams, and more, to measure and guide improvements to our simulation platform.
Compensation
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $193,000 to $328,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.
Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to
[email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Responsibilities
You will derive requirements and perform system verification/validation for simulation frameworks and tools.You will drive planning and execution by decomposing system needs into projects, tools, and/or features that deliver incremental value to teams and customers.You will build metrics and tools which measure and continuously monitor simulation validity in alignment with company objectives.You will lead analyses of tools/frameworks and communicate results across stakeholders, driving continuous improvement to software components.You will collaborate with Engineering Managers to ensure design, implementation, and programs are on track, and regularly drive consensus among diverse partners on technical projects.You will develop clear proposals and design documents for large-scope or multi-functional initiatives.You will design and build statistically-sound analyses, sampling methods, validation criteria, and development processes for building highly relevant datasets for evaluation applications.You will build tools to mine large-scale logs and simulated data for the most interesting situations.Your typical workload: 30% validation strategy 30% coding, 40% dataset development and statistical analysis. Qualifications
8+ years of experience in decomposing and analyzing large, complex systems.Experience in systems engineering, requirements authoring, system analysis, and validation/testing.Experience developing, specifying, and/or validating simulation-based testing technologies for autonomous, robotics, or other complex integrated systems.Fluent in data-based and analytical engineering problem-solving practices, including using paretos and root cause analysis.Databricks, Jupyter Notebooks experience.Proficient with Python, SQL, or similar for analysis of large datasets.BS, MS, or Ph.D. in Computer Science, Mechanical Engineering, Robotics, or equivalent experience