Senior Computer Vision Engineer, Phantom AI

• This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration
• 3–5+ 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
• 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
• Practical experience with data pipelines, distributed training, and machine learning experiment management tools
• Proven ability to work effectively in a collaborative, cross-functional team environment

Desirable

• We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS)
• The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms
• Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems
• Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms
• Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions
• Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment
• Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs
• Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration
• Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management