Senior Machine Learning Engineer - Motion Planning & Model Introspection

Job Description

Our team designs, builds, and maintains software supporting the introspection of machine learning-based motion planners. We are responsible for developing introspection techniques and providing autonomy software engineers tooling used to understand and debug motion planning behavior.

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.

In this role, you will:

Lead new initiatives to introspect the output of machine learning motion planning models. You will both utilize existing cutting edge techniques as well as develop novel introspection techniques.

Design new architecture and implement new tools used to analyze machine learning model behavior.

Collaborate with engineers on Perception, Prediction, Planning, Machine Learning Model, and Visualization teams to enable development of behavior improvements.

Qualifications

MS or PhD in Computer Science, Machine Learning, or a related field

5+ years of industry experience in Machine Learning–experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation

Proficiency in Python and ML libraries (PyTorch, NumPy, Jax)

Strong understanding of Imitation and Reinforcement Learning concepts and motion planning search techniques

Familiarity with common learned model introspection techniques