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Software Engineer – Perception Algorithm
| Company | Lucid Motors |
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| Location | Newark, CA, USA |
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| Salary | $154000 – $211750 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Mid Level, Senior |
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Requirements
- Proficient in Python and C++ for real-time and high-performance computing.
- Skilled in Linux development, debugging, and system optimization.
- Experience with sensor fusion (e.g., Kalman Filters, Bayesian Inference).
- Strong knowledge of probabilistic models, SLAM, and Kalman filtering.
- Familiar with deep learning frameworks (TensorFlow, PyTorch).
- Knowledgeable about ROS, middleware frameworks, and real-time constraints.
- Vehicle testing experience including data collection and algorithm validation.
- Developed tools for data visualization, debugging, and automated evaluation.
- Excellent communication and teamwork skills.
- Bachelor’s or Master’s in Computer Science, Electrical Engineering, Robotics, or related field.
- 3+ years relevant work experience or Ph.D. for senior roles.
Responsibilities
- Develop and optimize perception algorithms for Level 2/3 autonomous driving systems using camera, LiDAR, and RADAR data.
- Implement and enhance vehicle localization using GNSS, IMU, LiDAR, and visual odometry.
- Design and develop occupancy grid fusion techniques for environment modeling and obstacle detection.
- Implement drivable space estimation using classical methods (e.g., Bayesian models, rule-based) and deep learning approaches (e.g., BEV segmentation, Transformer models).
- Develop custom tools for sensor data visualization, debugging, and algorithm evaluation.
- Write high-performance, real-time software for deployment on embedded automotive platforms (e.g., NVIDIA Orin, Xavier).
- Collaborate with cross-functional teams to ensure seamless integration and robust implementation.
- Test, release, and deploy perception algorithms into Lucid production programs.
- Support the validation and verification of perception algorithms using prototype and pre-production vehicles.
- Propose software algorithms to enhance future autonomous driving capabilities.
Preferred Qualifications
- Multi-modal sensor fusion experience for automotive applications.
- Hands-on HD maps, BEV-based perception, and occupancy grid mapping.
- Understanding of deep learning architectures, including Transformer models.
- Deployed models on NVIDIA Jetson Orin, Xavier, or similar hardware.
- Knowledge of CAN bus, automotive networks, and vehicle interfacing.
