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Principal Machine Learning Engineer

California, United States (Hybrid)

Principal Machine Learning Engineer

21 Hours ago • 10 Years +

About the job

Summary_{By Outscal}

Lead the development of ML algorithms for autonomous driving behavior prediction, simulation, and validation. Requires expertise in Deep Learning, production ML pipelines, C++/Python, and strong mathematical skills. Collaborate with Perception, Planning, and Simulation teams.

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance.

As a Principal ML Engineer, you will lead the development of machine learning algorithms that can range from influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with teams specializing in Perception, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects.

Responsibilities

Develop new algorithms to model the future behavior of our own vehicle’s future actions, both in predicting our driving trajectories and estimating their quality in relation to our goals of safety, progress, and comfort
Build the foundation models for the on-vehicle and offline applications
Develop new algorithms to apply generative deep learning to simulation to improve the realism of our offline validation systems
Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
Provide technical mentorship to the broader group of ML developers at Zoox
Collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments

Qualifications

BS, MS, or PhD degree in computer science or related field
Experience with training and deploying Deep Learning models
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Fluency in C++ or Fluency in Python with a basic understanding of C++
Extensive experience with programming and algorithm design
Strong mathematics skills
10+ years of experience

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 $296,000-$451,000. 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.

$296.0K - $451.0K/yr (Outscal est.)

$373.5K/yr avg.

Foster City, California, United States