Vision engineer
1 day ago
Responsibilities:
• Develop and deploy real-time vision systems for object detection, scene understanding and gesture recognition.
• Fine-tune and integrate LLMs for task planning, dialogue, memory, and reasoning in robotic workflows.
• Fuse multimodal data (vision, audio, proprioception) to build situational awareness and contextual understanding.
• Work on embodied AI, linking physical world inputs with cognitive reasoning to drive robotic decision-making.
• Collaborate with hardware, software, and control teams to integrate AI modules on the robot's edge-computing stack.
• Optimize models for real-time performance on embedded or edge devices (e.g., NVIDIA Jetson, Intel Movidius, etc.).
• Conduct experiments, evaluations, and benchmarking in simulation and real-world test environments.
Skills Needed:
• Computer Vision (Object Detection, Scene Understanding, Gesture Recognition)
• Deep Learning (CNNs, RNNs, Transformers, Multimodal Learning)
• LLM Fine-Tuning and Integration (e.g., GPT, LLaMA, Mistral)
• Embodied AI and Cognitive Reasoning
• Sensor Fusion (Vision, Audio, Proprioception)
• Edge AI Deployment (NVIDIA Jetson, Coral TPU)
• Model Optimization (Quantization, Pruning, TensorRT, ONNX, OpenVINO)
• Programming Languages (Python, C++, CUDA)
• ML/DL Frameworks (PyTorch, TensorFlow, OpenCV, Transformers
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