We are looking for an experienced Perception Machine Learning Algorithm Engineer to join 
our ADAS/Autonomous Driving team. This position requires a highly skilled professional 
with a strong background in 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.

Role and Responsibilities
• Develop and optimize perception algorithms for Level 2/2+/3 autonomous driving 
systems using camera, LiDAR and radar data.
• Design and implement cutting-edge deep learning algorithms for 2D/3D object 
detection, segmentation, tracking, and multi-task learning.
• Design, train, and evaluate machine learning or deep learning models for detecting 
vehicles, pedestrians, and other road users from sparse radar data.
• Fuse radar detections with data from camera, lidar, and/or inertial sensors.
• Research and integrate BEV-based transformer models for perception tasks.
• Collaborate with cross-functional teams to ensure seamless integration and robust 
implementation.
• Deploy, test and release perception algorithms into Lucid production programs.
• Support the validation and verification of perception algorithms using prototype and 
pre-production vehicles.
• Propose innovative software algorithms to enhance future autonomous driving 
capabilities.

Required Qualifications
• Strong theoretical foundations and expertise in deep learning algorithms, including 
dynamic and static object detection, tracking, and segmentation.
• Strong experience with 3D point cloud processing, preferably with radar data.
• Familiarity with common radar data formats (e.g., raw detections, clustered point 
clouds, heatmaps).
• 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 and deployment toolchains, ONNX, TensorRT.
• Ability to design and construct evaluation pipelines to unit-test ML models under 
diverse conditions and environments.
• Excellent communication skills and a strong team player.
• Bachelor’s degree in Computer Engineering, Electrical Engineering, Automotive 
Engineering, Mechanical Engineering, or a related field.
• Minimum of 3 years of relevant work experience, or a Ph.D. in a related field for a 
senior position.
• Advanced degrees are preferred.

Preferred Qualifications
• Experience developing BEV transformer models for perception.
• Experience with automotive radar (e.g., Continental, Bosch, Aptiv)
• Background in multi-sensor fusion (radar-camera, radar-IMU).
• Proficiency in C++ with experience writing efficient, maintainable code.
• Practical, hands-on approach to solving complex problems in autonomous driving.
• Experience in testing and validating perception systems in real-world conditions.
• Experience working in agile development teams.
• Expertise in component and system integration, testing, and verification at the 
system and vehicle levels