Description
The Core Data Science team owns a suite of products that provide actionable insights to the on-vehicle software teams. In particular, our scenario search tools are used by teams developing and validating Zoox’s on-vehicle AI stack to estimate and analyze event rates at scale, enabling the launch of an autonomous mobility service. Our team also works closely with dedicated Data Science teams to develop key driving behavior metrics and direct new feature development, using large scale data from our autonomous driving fleet and simulations.
You are a good fit for our team if you are a software engineer with a propensity for big data analysis, or a data engineer / scientist with an understanding of and enthusiasm for sound software engineering practices. You will join a diverse, experienced team with rapidly growing scope and responsibility while also having access to a uniquely valuable data set in the autonomous vehicle industry.
In this role, you will:
- Collaborate with our software and systems engineering teams to build and support core scenario search capabilities for Zoox
- Work alongside our data engineering and data science teams to develop and use robust large scale data solutions
- Identify key areas of investment for our vehicle software teams
- Establish best practices and processes around data-driven decision-making
Qualifications
- Extensive experience with large-scale data processing frameworks, with preference for Spark or Hadoop
- Software development experience in a production environment, with preference for Scala, Python, or Java; or demonstrated experience learning new programming languages
- Familiarity with any version control system, with preference for Git
- Experience designing metrics and building mechanisms that deliver robust, actionable insights
- Good communication and collaboration skills
Bonus Qualifications
- Experience training and deploying ML models to large scale production use cases
- Basic familiarity with C++
- Experience with geospatial data analysis
- Familiarity with or exposure to experimentation platforms
- Basic familiarity with any autonomous vehicle competency, e.g. perception, localization, prediction, planning, or controls
Compensation:
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary range for this position is $192,000 to $273,000. A sign-on bonus may be offered as part of the compensation package. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
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 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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