Senior/Staff Software Engineer - Learned Trajectory Machine Learning Engineer

Posted:
11/6/2024, 3:39:47 PM

Location(s):
Foster City, California, United States ⋅ California, United States

Experience Level(s):
Expert or higher ⋅ Senior

Field(s):
AI & Machine Learning ⋅ Software Engineering

Workplace Type:
Hybrid

Pay:
$115/hr or $239,200 total comp

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.
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 $230,000 to $332,000. 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.

Zoox

Website: https://zoox.com/

Headquarter Location: Foster City, California, United States

Employee Count: 1001-5000

Year Founded: 2014

IPO Status: Private

Last Funding Type: Convertible Note

Industries: Autonomous Vehicles ⋅ Machine Learning ⋅ Robotics ⋅ Transportation