Executive Director - Gen AI & ML Engineer

We are seeking an Executive Director to help lead the design, development, and deployment of enterprise-scale Generative AI and Machine Learning solutions. This is a highly technical, hands‑on leadership role focused on building AI platforms, production ML infrastructure, and scalable LLM‑powered applications that drive adoption across a large global organization.

The ideal candidate combines deep machine learning expertise, strong software engineering fundamentals, and a track record of leading teams while remaining close to the technology. This role is best suited for someone who enjoys taking ideas from concept to production and thrives in fast‑paced, high‑impact environments.

• Lead the design and delivery of production‑grade AI and machine learning platforms
• Build scalable applications powered by LLMs, Generative AI, and foundation models
• Develop AI‑powered solutions including chatbots, agents, workflow automation tools, and knowledge retrieval systems
• Design and deploy APIs, services, and infrastructure supporting enterprise AI adoption
• Partner with engineering, cloud, and research teams to bring AI solutions into production
• Architect highly scalable systems capable of supporting large user populations
• Drive rapid prototyping and proof‑of‑concept development while maintaining production quality standards
• Optimize model serving, inference, reliability, scalability, and performance
• Mentor and lead teams of ML Engineers, Applied Scientists, and Software Engineers
• Establish engineering best practices and influence technical strategy
• Work directly with business leaders to identify and deliver high‑impact AI solutions

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related quantitative discipline
• Experience leading teams of Machine Learning Engineers and/or Applied Scientists
• Strong hands‑on engineering background with the ability to code, prototype, and deploy solutions independently
• Experience building and deploying production machine learning systems from the ground up
• Deep understanding of LLMs, Generative AI, NLP, Computer Vision, or related AI disciplines
• Experience with AWS, Kubernetes, and cloud‑native architectures
• Strong knowledge of distributed systems and large‑scale application design
• Excellent understanding of machine learning fundamentals, optimization, and statistics
• Strong communication skills with the ability to influence both technical and executive stakeholders

• Experience building AI infrastructure or ML platforms
• Experience with Ray, Deep Speed, Horovod, or distributed training frameworks
• Experience with RAG architectures, AI agents, and vector databases
• Hands‑on experience with model fine‑tuning, quantization, and inference optimization
• Background in high‑growth technology companies, AI startups, or large‑scale AI organizations
• Published research in Machine Learning, NLP, Computer Vision, or related fields

The ideal candidate is an engineering‑focused AI leader who has built production machine learning systems y are equally comfortable discussing model architecture, distributed systems, cloud infrastructure, and business outcomes. They have a proven track record of turning ideas into production‑ready solutions and thrive in environments that demand speed, ownership, and innovation.

• Not a traditional Data Scientist position
• Not a research‑only role
• Not a people‑management role disconnected from technology
• Not a software engineering role with minimal AI responsibilities
• Not focused solely on experimentation or proof‑of‑concepts

Onsite presence is expected.

We’re specifically looking for builders. The strongest candidates will have personally designed, built, and deployed production AI or ML infrastructure, led high‑performing technical teams, and demonstrated the ability to move quickly from concept to production. If you’ve built scalable AI platforms, owned ML services in production, and enjoy solving complex problems with a startup mindset, we’d love to connect.