Senior/Staff Machine Learning Engineer - AutoML

Qualifications*

• BS/MS/PhD in Machine Learning, Computer Science or equivalent experience

• Experience in scaling optimization systems in production (e.g. hyperparameter tuning)

• 4+ years of relevant experience

• Fluency in Python

• Experience with distributed systems

• 5+ years of relevant experience

Bonus Qualifications

• Fluency in C++

• Experience with black-box optimization and its application to hyperparameter tuning

• Experience with multi-objective optimization

• Experience with autonomous vehicles or robotics

• Experience building large-scale software services on the cloud

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 $221,000 to $319,000. 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.

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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.