Staff Behavior Planning Engineer, Autonomous Driving

Lucid MotorsNewark, CA

$171,500 - $251,460 / year

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Overview

Schedule

Full-time

Career level

Senior-level

Compensation

$171,500-$251,460/year

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Job Description

Leading the future in luxury electric and mobility

At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.

We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.

Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

Responsibilities:

· Design, prototype, test, and deploy state-of-the-art behavior planning algorithms for autonomous and assisted driving features.

· Develop and implement decision-making, trajectory and route planning, and optimization-based planning frameworks.

· Collaborate closely with perception, controls, localization, and systems teams to ensure robust and efficient integration of planning software.

· Drive innovation through the invention of novel algorithms and features that elevate the safety, comfort, and intelligence of Lucid vehicles.

· Support the validation and verification of behavior planning components in simulation, hardware-in-the-loop (HIL), and on-road testing environments.

Required Qualifications:

· MS degree in Robotics, Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field (or equivalent experience).

· 2+ years of professional experience, or a Ph.D. in a relevant discipline.

· Strong C++ programming skills with a solid understanding of software engineering best practices.

· Deep knowledge of decision-making algorithms such as graph/tree search methods or AI-based planners.

· Experience with motion and behavior planning concepts including decision-making under uncertainty, optimization techniques, trajectory generation, and route planning.

· Hands-on experience with embedded systems integration in robotics or automotive domains.

· Strong communication and problem-solving skills.

Preferred Qualifications:

· Experience with middleware systems such as ROS or DDS.

· Proficiency in scripting languages such as Python, Bash.

· Experience with simulation tools (e.g., Gazebo, CARLA) and frameworks for testing autonomous systems.

· Experience and understanding of deep learning frameworks (e.g., TensorFlow, PyTorch).

· Experience and knowledge of imitation/reinforcement learning techniques.

· Familiarity with version control systems (e.g., Git) and modern development workflows.

· Prior work on scenario-based testing, MIL/SIL/HIL environments, or automated test frameworks.

· Exposure to CI tools such as Jenkins or GitLab CI.

Salary Range: The compensation range for this position is specific to the locations listed below and is the range Lucid reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and training; certifications; and other relevant business and organizational factors.

Additional Compensation and Benefits: Lucid offers a wide range of competitive benefits, including medical, dental, vision, life insurance, disability insurance, vacation, and 401k. The successful candidate may also be eligible to participate in Lucid’s equity program and/or a discretionary annual incentive program, subject to the rules governing such programs. (Cash or equity incentive awards, if any, will depend on various factors, including, without limitation, individual and company performance.)

Base Pay Range (Annual)

$171,500—$251,460 USD

By Submitting your application, you understand and agree that your personal data will be processed in accordance with our Candidate Privacy Notice. If you are a California resident, please refer to our California Candidate Privacy Notice.

To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes.

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FAQs About Staff Behavior Planning Engineer, Autonomous Driving Jobs at Lucid Motors

What is the work location for this position at Lucid Motors?

This job at Lucid Motors is located in Newark, CA, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.

What pay range can candidates expect for this role at Lucid Motors?

Candidates can expect a pay range of $171,500 and $251,460 per year.

What employment applies to this position at Lucid Motors?

Lucid Motors lists this role as a Full-time position.

What experience level is required for this role at Lucid Motors?

Lucid Motors is looking for a candidate with "Senior-level" experience level.

What benefits are offered by Lucid Motors for this role?

Lucid Motors offers following benefits: Health Insurance, Dental Insurance, Vision Insurance, Disability Insurance, Life Insurance, Paid Vacation, and 401k Matching/Retirement Savings for this position. Actual benefits may vary depending on the employer's policies and employment terms.

What is the process to apply for this position at Lucid Motors?

You can apply for this role at Lucid Motors either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.