Senior/Staff Computer Vision Engineer - Deep Learning Focus

About the company Phantom AI is an automotive technology company building cost-effective L2/L3 Advanced Driver Assistance Systems (ADAS) to reduce the burden of everyday driving and make roads safer for everyone. Their main customers are Tier 1 automotive manufacturers focused on delivering L2/L3 solutions, with a long-term vision of full autonomy. Phantom AI differentiates itself through state-of-the-art technological know-how and real-world experience shipping ADAS systems at volume production scale. About the role Phantom AI is seeking a Senior/Staff Computer Vision Engineer with a Deep Learning focus to drive the development and deployment of advanced perception models for ADAS. The role involves designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded automotive platforms. This is a hybrid position (4 days in-office, 1 day remote) based in Mountain View, CA. Responsibilities - Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems. - Maintain and improve existing models by optimizing performance, refining architecture and algorithms. - Perform root cause analysis of production issues and develop sustainable, high-quality solutions. - Optimize model performance for latency, efficiency, and resource utilization on real-time embedded deployment. - Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs. - Collaborate with data engineering, annotation, and platform engineering teams for seamless model integration. Requirements - 3-5+ years of experience developing, training, validating, and deploying deep learning-based perception models for ADAS or computer vision applications. - Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or equivalent industry experience. - Strong proficiency in Python and expertise in PyTorch (preferred) or TensorFlow for large-scale model development. - In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design. - Practical experience with data pipelines, distributed training, and ML experiment management tools. Nice to have - Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon). - Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation. - Ph.D. in Computer Science, AI, or related field. - Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP). Benefits & perks - Medical, dental, and vision coverage. - Paid Time Off, FSA, and 401K. - Office snacks and reimbursable meals. Compensation $180,000 - $240,000 base salary.