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.
Duties and Responsibilities:
Team Leadership: Lead and mentor a team of machine learning and AI engineers, fostering a culture of innovation, continuous learning, and excellence.
Strategic Roadmap: Define and execute the comprehensive ML/AI strategy and roadmap, aligning it with the company's overall business objectives and long-term vision.
End-to-End Deployment: Oversee the end-to-end development and deployment of machine learning and artificial intelligence models, from ideation and experimentation to production and monitoring.
Cross-Functional Collaboration: Collaborate with product, engineering, data platform, and other cross-functional teams to identify new opportunities for leveraging traditional ML and advanced AI.
AI Innovation & Adoption: Stay up-to-date with the latest advancements in machine learning and AI (including Generative AI, Large Language Models, and computer vision), and drive the adoption of new technologies and best practices.
AI Governance & Ethics: Establish and champion frameworks for responsible AI, ethics, data privacy, and compliance across all model deployments.
Stakeholder Communication: Communicate the complex value and business impact of machine learning and AI initiatives to senior leadership, C-suite executives, and other stakeholders.
Roadmap Influence: Influence product and operational roadmaps with actionable data insights and active AI deployments.
Data Strategy: Build a strategic learning roadmap based on data observations, strategic imperatives, and developed hypotheses, while managing robust data and feature pipelines.
Education: Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field.
Domain Experience: 10+ years of experience in machine learning and AI, with a proven track record of building, scaling, and deploying production-level models.
Leadership Experience: 5+ years of experience leading and managing high-performing machine learning or AI engineering and research teams.
Technical Expertise: 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).
Programming & Frameworks: Strong programming skills in Python and deep experience with ML/AI frameworks such as TensorFlow, PyTorch, or Hugging Face.
Core Skills: Excellent leadership, communication, and project management skills.
Organizational Scaling: Demonstrated success in building and scaling ML/AI organizations from the ground up, including hiring, budgeting, and tool/vendor selection.
Executive Presence: 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.
Infrastructure Knowledge: High-level architectural understanding of MLOps, LLMOps, cloud infrastructure (AWS/GCP/Azure), and the full model development lifecycle (MDLC).
Minimum Qualifications:
Communication Skills:
Writing, Talking/Hearing on the phone (Continually=67-100% of workday)
Environment Requirements:
Remote/Home office (Continually=67-100% of the workday)