Machine Learning Engineer, Perception

We are seeking a highly skilled Machine Learning Engineer with deep expertise in developing Bird’s Eye View (BEV) fusion models using multimodal sensor inputs, particularly LiDAR. You will play a central role in designing scalable perception algorithms that integrate data from camera, LiDAR, and radar sensors to support autonomous driving and 3D scene understanding.

Responsibilities:

• Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs.
• Benchmark perception models using large-scale datasets and well-defined quantitative metrics.
• Collaborate cross-functionally with research, data, and deployment engineers to refine models and support real-world applications.
• Maintain a strong focus on performance, robustness, and scalability for deployment in production systems.

Required Skills:

• Master’s or Ph.D. in AI, Computer Science, Electrical Engineering, Robotics, or a related field.
• Proficiency in Python and experience building deep learning pipelines.
• Strong expertise in PyTorch, TensorFlow, or JAX.
• Proven experience with LiDAR-based 3D perception and BEV representation models
• Deep understanding of multimodal sensor fusion architectures and techniques.
• Familiarity with camera, LiDAR, and radar modalities and their synchronization, calibration, and integration in perception pipelines.
• Solid foundation in computer vision, deep learning, and 3D geometry.

Preferred Skills:

• Industry or academic experience in autonomous vehicle perception, robotics, or related areas.
• Hands-on experience developing deep learning models in real-world or production environments.
• Experience with distributed training, high-performance computing, or GPU acceleration.