Phantom AI is seeking a Senior Deep Learning Engineer to develop and deploy advanced perception models for Advanced Driver Assistance Systems (ADAS), aiming to create cost-effective L2/L3 solutions to improve road safety and reduce driving burden.
Requirements
- 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.
- 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.
- 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.
Responsibilities
- 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.
Other
- Proven ability to work effectively in a collaborative, cross-functional team environment.
- Hybrid work model (3x in office, 2x remote per week).
- Equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type.
