Head of AI Engineering

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Requirements:

• PhD or MS in AI, Computer Vision, Machine Learning, or a related field, coupled with 8+ years of industry experience in AI/ML, including a strong background in both Convolutional Neural Networks (CNNs) and Large Language Models (LLMs).
• Proven expertise in computer vision models (e.g., YOLO, EfficientNet, etc.) and LLMs (e.g., GPT, LLaMA, Claude, Gemini), including experience with fine-tuning techniques for both.
• Strong programming skills in Python and hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and libraries (Hugging Face Transformers).
• Hands-on experience in developing and deploying multi-modal AI systems that integrate text, vision, and structured data (at work or at home).
• Knowledge of edge AI techniques, real-time inference, and low-latency model optimization.

Responsibilities:

• Proven leadership in defining and executing a comprehensive AI strategy, including roadmap development and successful integration of AI solutions into core product offerings.
• Extensive experience architecting and developing compound AI systems, specifically combining Computer Vision (CNNs) and Large Language Models (LLMs) to extract insights from both structured and unstructured data sources.
• Deep expertise in AI model design, training, and optimization, including hands-on experience with real-time video analysis using CNNs and fine-tuning LLMs for domain-specific applications (e.g., safety intelligence, risk assessment).
• Demonstrated ability to design and deploy scalable AI architectures across diverse environments, including on-premise, edge devices, and cloud platforms, with a strong understanding of MLOps principles and practices.
• Experience building and leading MLOps & AI Infrastructure, building pipelines, implementing AI model monitoring, and integrating continuous learning to improve AI accuracy and efficiency.
• Strong track record of cross-functional collaboration, with proven ability to work effectively with engineering, product, and data science teams to deliver AI-driven solutions, while ensuring compliance with relevant regulatory and ethical AI standards.