Software Engineer - Fail Operational Planning

Zoox

2600

Foster City, CA, USA

Posted on: 2024-07-15

Category: emobility

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Employment type:

Full time

Experience required:

Intermediate

Salary

Salary not provided

About the company:

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

The Fail Operational Planning team at Zoox works to ensure that the robot continues to operate effectively, even in the presence of minor compartmentalized failures or degraded capabilities. The focus of the team includes trip progress, vehicle uptime metrics, and correspondingly a better customer experience. This is a cutting-edge problem which requires teamwork and collaboration across a diverse group of experts including Planner, Perception, Prediction, Hardware, and more.

On this team, you will contribute to the next generation of algorithmic advancements to expand our robot’s ability to drive in some of the most complex scenarios. We are looking for an engineer who is excited to understand the interdependencies within the driving stack and takes ownership of their projects and has a holistic product focused approach towards development.

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 $165,000 to $264,000. 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.

In this role, you will:

Create principled algorithmic improvements to specific areas of driving behavior and implement those changes in our code base.

Collaborate cross-functionally to identify failure modes of the system, and develop strategies and intelligent behaviors to mitigate the performance degradation.

Architect and implement scalable solutions ensuring seamless integration with the rest of the driving stack.

Partner with validation teams to define and execute tests for developed algorithms.

Qualifications:

Master's degree in Computer Science or related field

Fluency in C++

Extensive experience with programming and algorithm design

Understanding of vehicle kinematics

3+ years of experience in a related field

Bonus Qualifications

PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or related field

Experience shipping products to market (commercial robotics, drones, consumer devices etc.)

Demonstrated ability to create real-time motion planning algorithms in a cross-functional team

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