Senior Computer Vision Engineer (Deep Learning)

Join PhantomAI, Harbinger's ADAS division, as a Senior Computer Vision Engineer. In this role, you will design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems. You will also optimize model performance for real-time embedded deployment and collaborate closely with various teams to ensure smooth data flow and seamless model integration. This position is based in Mountain View, CA and offers comprehensive health coverage, an annual vacation stipend, early-stage stock options, flexible PTO, and paid lunches and dinners.

• Design and implement advanced deep learning architectures to enhance perception capabilities within Advanced Driver Assistance Systems (ADAS).
• Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms.
• Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration.
• Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods
• 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
• Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience
• Strong proficiency in Python and a deep understanding of software design principles and development best practices
• Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation
• Proven ability to work effectively in a collaborative, cross-functional team environment
• 5+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications
• In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design
• Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus
• Practical experience with data pipelines, distributed training, and machine learning experiment management tools
• Strong programming experience in Python and/or C++ within Linux development environments
• Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP)