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.

Role and Responsibilities

• Research, design, implement, optimize and deploy computer vision algorithms for driving and parking features
• Implement high-quality automotive grade software code compliant to automotive quality and safety standards
• Integrate software stack with the overall perception software stack for running onboard perception system with excellent performance and high fault tolerance
• Test, release, and launch the perception algorithm into the production programs
• Contribute to the ADAS software roadmap, strategic planning, and development timeline
• Contribute to the systems requirements and identify performance metrics for individual components
• Conduct on-road ADAS software testing and create test plans to support algorithm development

Required Qualifications

• Bachelors in Computer Engineering, Electrical Engineering, Robotics, Mechanical Engineering
• 5 years of related experience
• Extensive knowledge and applied experience in 3D computer vision, multi-view geometry, SfM/SLAM
• Strong skills in camera calibration, linear algebra, numerical optimization, factor graph representations and statistical estimation theory. Familiarity with OpenCV and image processing.
• A solid foundation in math and robotics to propose creative solutions for autonomous systems
• Proficient in C++ and In-depth knowledge in object-oriented programming, algorithms, data structures, and software design skills
• Excellent communication skills and good team player

Preferred Qualifications

• Masters in Computer Vision, Computer Engineering, Electrical Engineering, Robotics, Mechanical Engineering
• 3 years related experience Or Ph.D. with no experience.
• Experience using optimization libraries such as GTSAM, Ceres, g20, etc.
• Experience with real time operating systems (e.g., QNX, Ubuntu, etc.)
• Experience working with different sensor modalities such as GPS/IMU, ultrasonic, wheel odometry, etc.
• Experience in working in agile development teams

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)

$163,700—$272,800 USD

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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.