Zoox
Data Scientist, Machine Learning
Zoox - Foster City, California, United States, 94420
Work at Zoox
Overview
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Overview
The Data team leverages data from our autonomous vehicles and operations to determine autonomy and service readiness. We provide the foundation for strategic decision-making at Zoox. You will be responsible for partnering with our AI, simulation, and mission assurance teams to drive improvements, inform development, and identify high leverage projects on our path towards autonomy. You will be able to drive how Machine Learning is leveraged for offline use. You will play a key role in enabling Zoox to develop and scale with a data-driven environment.You will join a diverse, experienced team with rapidly growing scope and responsibility while also having access to one of the most unique data sets in the autonomous vehicle industry.
In this role, you will:
Build scalable ML pipelines including experimentation, production and monitoring Build capabilities which can be leveraged across the company for search, similarity and exposure computations Collaborate with our behavior analysis teams to develop models to quantify and qualify our driving Identify key areas of investment for our perception, prediction, and planning teams Establish best practices and statistical rigor around data-driven decision-making Qualifications
Bachelor's, Master's or PhD in CS, statistics, mathematics or relevant fields Fluency in Python or Scala Familiarity with SQL Experience with Spark or large-scale data analysis Experience designing metrics, building mechanisms to fuel business insights, and driving decision-making at various levels in an organization Bonus Qualifications
Experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training Basic fluency in C++ Experience with geospatial data analysis Familiarity with or exposure to experimentation platforms 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 $178,000 to $294,000. 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. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com 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.
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Build scalable ML pipelines including experimentation, production and monitoring Build capabilities which can be leveraged across the company for search, similarity and exposure computations Collaborate with our behavior analysis teams to develop models to quantify and qualify our driving Identify key areas of investment for our perception, prediction, and planning teams Establish best practices and statistical rigor around data-driven decision-making Qualifications
Bachelor's, Master's or PhD in CS, statistics, mathematics or relevant fields Fluency in Python or Scala Familiarity with SQL Experience with Spark or large-scale data analysis Experience designing metrics, building mechanisms to fuel business insights, and driving decision-making at various levels in an organization Bonus Qualifications
Experience with training frameworks like PyTorch, leveraging GPUs efficiently for distributed model training Basic fluency in C++ Experience with geospatial data analysis Familiarity with or exposure to experimentation platforms 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 $178,000 to $294,000. 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. Follow us on LinkedIn Accommodations If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com 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.
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