Computer Vision Engineer

Develop proof-of-concept (POC) computer vision systems for intelligent mobility and in-vehicle applications. The role focuses on rapidly evaluating, implementing, and deploying state-of-the-art computer vision and AI technologies on vehicle-grade edge computing platforms, bridging cutting-edge research and real-world intelligent mobility systems. Responsibilities

• Develop proof-of-concept systems using state-of-the-art AI and computer vision technologies.
• Design and implement computer vision algorithms for object detection, tracking, semantic/instance segmentation, 3D scene understanding, visual localization, mapping, driver and occupant monitoring, and behavior recognition.
• Build solutions using modern AI approaches including Vision Transformers (ViT), Vision-Language Models (VLMs), Multimodal AI, Foundation Models, Self-Supervised Learning, and Generative AI.
• Evaluate and adapt the latest research papers and open-source models to automotive and intelligent mobility applications.
• Integrate camera, vehicle, and sensor data to create innovative AI-driven applications.
• Develop and integrate AI software on embedded and edge computing platforms for in-vehicle applications.
• Design real-time perception systems operating under vehicle constraints including compute, memory, latency, power consumption, and robustness.
• Optimize AI models for deployment on automotive SoCs, GPUs, and AI accelerators.
• Prototype and evaluate end-to-end systems on vehicle platforms, embedded devices, and research vehicles.
• Develop software for deployment and demonstration in vehicle-based proof-of-concept platforms.
• Evaluate tradeoffs among accuracy, latency, memory footprint, and operational robustness.
• Collaborate with researchers, software engineers, and system engineers to realize innovative concepts and demonstrations.
• Stay up to date with emerging trends in computer vision, multimodal AI, edge AI, and intelligent mobility systems.

• Master''s degree or higher in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, or a related field.

• Strong background in Computer Vision and Machine Learning.

• Hands-on experience with PyTorch, TensorFlow, OpenCV, or similar frameworks.

• Experience implementing and training deep learning models including CNNs, Transformers, Vision Transformers (ViT), Vision-Language Models (VLMs), and multimodal architectures.

• Strong programming skills in Python and C++.

• Experience reading, reproducing, and extending recent AI/CV research publications.

• Familiarity with Linux development environments.

• Excellent verbal and written communication skills. Preferred Qualifications

• Experience with Foundation Models, Large Vision Models, and Multimodal AI systems.

• Experience with CLIP, SAM (Segment Anything), DINOv2, BEV-based perception models, or similar state-of-the-art vision technologies.

• Experience with Generative AI and synthetic data generation.

• Experience developing software on embedded Linux systems.

• Experience with CUDA, TensorRT, ONNX Runtime, OpenVINO, or comparable inference optimization frameworks.

• Experience optimizing and deploying AI models on edge devices and automotive computing platforms.

• Experience with NVIDIA Jetson, NVIDIA DRIVE, Qualcomm Snapdragon Ride, or similar embedded AI platforms.

• Experience with ROS/ROS2, sensor fusion, or robotic/automotive systems.

• Experience in automotive, robotics, autonomous systems, or intelligent transportation systems.

• Publications in leading AI, robotics, or computer vision conferences are a plus.

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