Senior/Staff Software Engineer - Learned Trajectory Machine Learning Engineer

zoox

| Foster City, CA, USA (Hybrid) | Full Time | 12 months ago

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Job Summary

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. The Learned Trajectory Machine Learning Engineer will be responsible for developing deep learned models that produce trajectories for vehicles to drive, collaborating closely with the Planner and Perception teams. This role involves developing new deep learning models using imitation learning and reinforcement learning, leveraging large-scale ML infrastructure, developing metrics and tools for error analysis, and collaborating with engineers on Perception, Planning, and Simulation.

Must Have

Develop new deep learning models for driving plans
Estimate quality of driving plans
Leverage ML infrastructure for solutions
Develop metrics and tools for error analysis
Collaborate with Perception, Planning, Simulation teams
BS, MS, or PhD in computer science or related field
Experience with transformer-based models and RL
Experience with production ML pipelines
Fluency in Python, basic C++
Extensive programming and algorithm design experience
Strong mathematics skills

Good to Have

Conference or Journal publications in ML or Robotics
Prior experience with Prediction or autonomous vehicles/robotics

Perks & Benefits

Paid time off
Zoox Stock Appreciation Rights
Amazon RSUs
Health insurance
Long-term care insurance
Disability insurance
Life insurance
Sign-on bonus may be offered

Job Description

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 Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior.

In this role, you will:

You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc.
You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
You will develop metrics and tools to analyze errors and understand improvements of our systems
You will 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 transformer-based model architectures and reinforcement learning
Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
Fluency in Python with a basic understanding of C++
Extensive experience with programming and algorithm design
Strong mathematics skills

Bonus Qualifications

Conference or Journal publications in Machine Learning or Robotics related venues
Prior experience with Prediction and/or autonomous vehicles or robotics in general

$230,000 - $317,000 a year

Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. 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.

7 Skills Required For This Role

Forecasting Budgeting Cpp Deep Learning Reinforcement Learning Python Algorithms Machine Learning

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