Description: Position Summary
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.
Requirements: Required Qualifications:
- 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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