The AI Driving Verification R&D group's mission is to design, prototype and productionize novel methods and tools for efficient modeling and simulations of complex systems at scale. We use recent advances in machine learning, statistics, optimization, and numerical methods to verify and validate our software and AI in the most challenging environments, and subsequently develop tools to enable other teams at Zoox to do the same.

Responsibilities

  • Research novel applications of machine learning and optimization to adversarial stress testing of our AI and software in simulations at scale
  • Develop optimization methods targeting black-box models, and methods for tackling the high dimensionality of parameter spaces and the actual problems themselves
  • Understand and quantify how uncertainty propagates through our systems
  • Build high-fidelity probabilistic models that reflect how real-world data looks like, and leverage them to understand the safety aspects of our simulations
  • Champion a rigorous approach to quantitative modeling and a production-level quality of your code
  • Work with other teams to enable them to use our tooling on their own

Qualifications

  • Minimum 4 years (PhD) or 6 years (Masters) of relevant work experience
  • Masters (research) or PhD in statistics, machine learning, optimization, operations research or similar, preferably with previous software engineering experience, such as significant internships.
  • Proficiency with Python's scientific stack, incl. machine learning and statistical frameworks (numpy, scipy, pandas, pytorch, pyMC3, etc.), and practical experience with distributed & GPU computing and modern SW development practices.
  • Experience with sample-efficient optimization, surrogate and other probabilistic modeling, design of experiments. Strong background in Bayesian statistics.
  • Proven track record of providing technical and thought leadership at the intersection of machine learning and optimization, and delivering impactful projects

Bonus Qualifications

  • Familiarity with C++ or Julia.
  • Rigorous verification & validation campaign experience, experience with statistical analysis of simulations, or practical experience in the autonomous driving industry
  • Relevant academic publications and strong track record of putting novel research methods into practice at scale
Vaccine Mandate

Employees working in this position will be required to be fully vaccinated against the COVID-19 virus. An applicant is considered fully vaccinated two weeks after their second dose in a 2-dose series, such as the Pfizer or Moderna vaccines, or two weeks after a single-dose vaccine, such as Johnson & Johnson’s Janssen vaccine. Applicants will be required to show proof of vaccination status upon receipt of a conditional offer of employment. That offer of employment will be conditioned upon, among other things, an Applicant’s ability to show proof of vaccination status. Please note the Company provides reasonable accommodations in accordance with applicable state, federal and local laws.

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.


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.