Senior Computer Vision Engineer - Deep Learning Focus

Phantom AI•Mountain View, CA

42d•$180,000 - $240,000•Hybrid

About The Position

At Phantom AI, we’ve built a team of incredibly talented and ambitious people challenging the norm in the automotive industry. We are building cost-effective L2/L3 solutions to reduce the burden of everyday driving and make the roads safe for everyone. For instance, we believe democratizing technologies such as Automatic Emergency Braking and Emergency Lane Support is the first priority before tackling a fully self-driving vehicle. Our main customers are Tier 1 automotive manufacturers who are focused on delivering L2/L3 solutions and in the future will deliver full autonomy. We differentiate ourselves from other autonomous driving startups through a combination of state-of-the-art technological know-how and real automotive experiences of shipping ADAS systems at a volume production scale. If you feel that you have the passion, commitment, and drive to challenge the status quo within the automotive industry, we would love to hear from you. 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. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration.

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.
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.

Nice To Haves

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.
Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus.
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)

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.