Artificial Intelligence Leader (AI Lead)
Canada, France, Germany, India, United Kingdom, United States
Negotiable
About this role
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We are looking for an AI Leader to technically lead a team of AI Engineers focused on Computer Vision and real-time video processing. The position is incorporated under the Staff Augmentation modality, with responsibility for the technical quality, the architecture of the solutions and the development of the team. Responsibilities Technically lead the AI Engineers team (definition of architecture, good practices and quality standards).
Define and validate the solution approach for AI video processing (models, pipeline, GPU infrastructure). Review and guide the design and implementation of Machine Learning / Computer Vision models. Ensure the performance and scalability of real-time processing of video streams.
Make technical decisions about CUDA/GPU usage and optimization. Act as a technical reference before business stakeholders, translating
Requirements
into viable solutions. Mentor and develop team members. Exclusive technical
Requirements
Solid and verifiable experience in Computer Vision. Experience leading AI/Machine Learning technical teams. Advanced knowledge of Python. Experience with OpenCV. Experience with Nvidia CUDA (programming and optimization on GPU). Experience in real-time processing of video streams. Experience with VisionPro.
Scope Note
This position requires specific experience and technical leadership in video, image processing, and GPU computing. Does not apply to profiles oriented exclusively to generative AI, LLMs or language/text processing (for example, expertise in ChatGPT or language models without background in computer vision). Desirable skills (not exclusive) Previous experience leading AI projects applied to cameras / video systems.
Knowledge of architecture of video processing systems at scale. Experience with deep learning frameworks (PyTorch, TensorFlow) and inference optimization (TensorRT, quantization). Competencies Technical leadership and mentoring capacity.
Strategic vision to connect the technical solution with the business. Effective communication with technical and non-technical stakeholders. Autonomy in architectural decision making.
Originally posted on Himalayas
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