Director, AI & Machine Learning

What you'll do

• Define and execute the multi-department AI/ML strategy and roadmap aligned with R&D, clinical, and commercial priorities.
• Lead the design, validation, and production scale-up of generative AI, foundation models, and agentic AI solutions.
• Establish scalable MLOps architecture including data quality, lineage, monitoring, and lifecycle governance to ensure reliable model delivery.
• Develop reusable engineering patterns and infrastructure to integrate scientific data into end-to-end research workflows.
• Implement responsible AI and model governance standards to balance innovation with regulatory, security, and privacy requirements.
• Recruit, mentor, and lead a high-performing team of ML engineers and technical professionals.
• Establish KPIs and metrics to measure the impact of AI capabilities on research productivity and operational efficiency.
• Communicate complex technical roadmaps and investment recommendations to senior executive stakeholders.

What we're looking for

• Must have a Doctorate with 4 years of experience, a Master’s with 8 years, or a Bachelor’s with 10 years in AI & Machine Learning leadership.
• Must have at least 4 years of experience managing people, leading teams, projects, programs, or directing resources.
• Expert knowledge in AI/ML engineering to set technical strategy for scientific research applications and production-grade workflows.
• Deep hands-on understanding of software engineering, cloud platforms, model serving, and scalable MLOps lifecycle operations.
• Ability to implement responsible AI governance and risk controls within regulated environments.
• Proven ability to communicate complex ML strategies and technical evidence to senior executive audiences.
• Proficiency with Python and modern ML/deep-learning frameworks like PyTorch, TensorFlow, or JAX.
• Relevant cloud, AI/ML, or MLOps certifications (preferred); experience in life sciences or agentic AI architectures (preferred).