Líder de Inteligencia Artificial (AI Lead)

Accountabilities Lead the AI engineering team from a technical perspective, defining architecture, engineering standards, best practices, and quality guidelines. Define and validate solution approaches for AI-powered video processing, including model selection, processing pipelines, and GPU infrastructure strategies. Review and guide the design, development, and implementation of machine learning and computer vision models. Ensure the performance, scalability, and reliability of real-time video processing systems. Make technical decisions related to CUDA usage, GPU optimization, and efficient AI model execution. Act as a technical reference for business and technical stakeholders, translating requirements into practical and scalable solutions. Mentor and support AI Engineers, fostering technical growth and continuous improvement within the team. Drive improvements in AI architecture, development processes, and production readiness. Requirements Proven experience in Computer Vision, with strong expertise in image processing, video analysis, and AI-driven visual solutions. Previous experience leading technical teams focused on artificial intelligence or machine learning projects. Advanced proficiency in Python and experience developing production-level AI solutions. Hands-on experience with OpenCV and computer vision development frameworks. Strong experience with Nvidia CUDA, including GPU programming and optimization techniques. Experience designing and optimizing real-time video processing systems and streaming pipelines. Experience with VisionPro or similar computer vision platforms. Ability to make architecture decisions and balance technical excellence with business requirements. Strong leadership, mentoring, and communication skills, with the ability to collaborate with both technical and non-technical stakeholders. Experience with AI projects involving cameras, video systems, or large-scale visual processing architectures is highly valued. Knowledge of deep learning frameworks such as PyTorch or TensorFlow, as well as inference optimization techniques like TensorRT and quantization, is a plus. Benefits Fully remote position with flexibility to work from anywhere. Opportunity to lead advanced AI projects involving computer vision and real-time video processing. Ability to influence technical strategy, architecture decisions, and AI engineering practices. Collaborative environment with talented AI and engineering professionals. Opportunity to work on innovative solutions using cutting-edge machine learning and GPU technologies. Continuous learning and professional growth opportunities within a highly technical environment.