Senior Director, Machine Learning and Artificial Intelligence

Role Description

The Senior Director of Machine Learning and Artificial Intelligence will be a strategic leader responsible for driving the development and execution of our machine learning and broader artificial intelligence initiatives. This individual will lead a team of machine learning engineers, AI engineers, and researchers to build and deploy cutting-edge ML models and AI solutions that create business value and enhance our products and services.

The ideal candidate will have a strong technical background in machine learning and artificial intelligence, extensive leadership experience, and a proven track record of delivering impactful enterprise-grade AI solutions. This role requires working closely with business partners while understanding and working within the constraints of the business to maintain a competitive technological edge.

Qualifications

• Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field.
• 10+ years of experience in machine learning and AI, with a proven track record of building, scaling, and deploying production-level models.
• 5+ years of experience leading and managing high-performing machine learning or AI engineering and research teams.
• Deep expertise in a variety of machine learning and AI techniques, including deep learning, natural language processing (NLP), reinforcement learning, and Generative AI/Large Language Models (LLMs).
• Strong programming skills in Python and deep experience with ML/AI frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Excellent leadership, communication, and project management skills.
• Demonstrated success in building and scaling ML/AI organizations from the ground up, including hiring, budgeting, and tool/vendor selection.
• Proven ability to link ML and AI initiatives to P&L outcomes, with experience presenting comprehensive AI strategies to C-suite executives or Board members.
• High-level architectural understanding of MLOps, LLMOps, cloud infrastructure (AWS/GCP/Azure), and the full model development lifecycle (MDLC).

Requirements

• Writing, Talking/Hearing on the phone (Continually=67-100% of workday)
• Remote/Home office (Continually=67-100% of the workday)
• Occasionally, less than 25% travel

Company Description