Senior Machine Learning Engineer (Perception)

• Ou 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
• 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
• Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
• Ensure team compliance with QMS, monitor quality, and drive process improvements

Benefits

• Unlimited PTO: Unlimited paid time off on top of company holidays to recharge and enjoy as needed
• Flexible working: Flexibile work arrangements and technology to help manage life’s demands at the office and remote
• Health benefits: Tiered options in medical, dental, and vision insurance to fit your unique needs
• Future building: Equity, 401k and FSA options for all eligible employees to help build for your future
• Professional development: Company-sponsored professional development opportunities such as conferences, training, and workshops
• Catered lunches: Daily catered lunches at both of our Santa Clara and Fremont offices- 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
• Solid foundation in computer vision, deep learning, and 3D geometry
• Proficiency in Python and experience building deep learning pipelines
• Strong expertise in PyTorch, TensorFlow, or JAX
• Deep understanding of multimodal sensor fusion architectures and techniques
• Proven experience with LiDAR-based 3D perception and BEV representation models
• Ph.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field
• Familiarity with camera, LiDAR, and radar modalities and their synchronization, calibration, and integration in perception pipelines
• Ph.D. new grad or Masters + 3 years industry experience
• Hands-on experience developing deep learning models in real-world or production environments
• Industry or academic experience in autonomous vehicle perception, robotics, or related areas
• Experience with distributed training, high-performance computing, or GPU acceleration