
Intern, Machine Learning Engineer, Summer 2026
Intern, Machine Learning, Perception Engineer, Summer 2026
We are currently seeking an ADAS Machine Learning Perception Engineer to intern on our ADAS team. This position requires a passionate student with a basic understanding of machine learning, computer vision, and perception algorithms, as well as solid programming expertise. As a member of Lucid’s Perception team, you will research, design, implement, optimize, and deploy state-of-the-art machine learning models that advance perception algorithms for autonomous driving. You will conduct literature reviews, develop and modify models to enhance performance, and contribute to the deployment of these models in production vehicles.
Our ideal candidate exhibits a can-do attitude and approaches his or her work with vigor and determination. Candidates will be expected to demonstrate excellence in their respective fields, to possess the ability to learn quickly and to strive for perfection within a fast-paced environment.
Role/Responsibilities:
- Develop machine learning and computer vision algorithms
- Benchmark the performance
- Propose innovative software algorithms to enhance future autonomous driving capabilities
- Design and implement cutting-edge deep learning algorithm prototype for surround view depth estimation and 3D object detection using cameras and lidar
- Curate and develop data pipeline, validate perception algorithms on Lucid’s data
Preferred Qualifications:
- Strong theoretical foundations and expertise in deep learning algorithms, including object detection, tracking, and segmentation
- Proficient in Python with a focus on clean, efficient, and scalable software development
- Comfortable working with large codebases and debugging complex machine learning models.
- Experience with PyTorch or other ML frameworks
- Excellent communication skills and a strong team player
Nice to have:
- Experience conducting research projects based on Autonomous Vehicles
- Exposure to image processing
- Experience developing BEV transformer models for perception
- Practical, hands-on approach to solving complex problems in autonomous driving
- Experience in testing and validating perception systems in real-world conditions
- Advanced degrees are preferred
Education:
- Field(s) of study: Electrical Engineering, Computer Science, Mechanical Engineering, Machine Learning or related fields
- Will consider undergrads Junior level or above: Pursuing a Bachelor’s or a master's degree
Program Details:
- Location: This position is in Newark, CA. You must be prepared to start onsite for your first day of employment.
- Availability: Full-time is preferred
- Anticipated Hours: 8:30am – 5:30pm
- Work Environment: Mix of office and bay.
- Compensation: Student compensation is based on location and current degree level, non-negotiable.
- Visa Sponsorship: Lucid may but is not obligated to sponsor foreign national employees requiring company sponsorship for U.S employment authorization.
- Medical Benefits: Dental and vision on day 1 for all interns working 30+ hours a week; medical for interns in California working 30+ hours a week.
- Housing/Transportation: You must provide your own living arrangements and transportation in the local area.
- Background Check: All offers of employment are contingent on clearing a background check.
Base Pay Range (hourly)
$50 - $70 USD
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.)
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.
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