Senior Lead ML Scientist - Molecular AI

Novo Nordisk•Lexington, MA

20h

About The Position

The Sr. Lead/Principal ML Scientist – Molecular AI will be a critical senior member of MolAI team. This is a senior, high-impact role within MolAI. You will work closely with the team to set scientific and technical direction for the team and to develop new AI-driven projects that influence R&D priorities across Novo Nordisk. You will be a visible technical champion for generative AI in molecular design, shaping strategy, mentoring colleagues, and driving cross-functional initiatives. You will join a team and organization that is investing heavily in AI-enabled discovery: significant experimental and data-generation resources are being directed toward producing the high-quality datasets that make advanced generative models and other AI methods most effective. In this environment you will have the opportunity to develop and deploy state-of-the-art models that directly inform experimental design and accelerate therapeutic discovery.

Requirements

M aster’s degree or PhD highly preferred. Minimum of Bachelor’s degree required.
Degree within within machine learning, computer science, computational chemistry or a related quantitative discipline preferred
Master’s Degree with 8+ years’ relevant experience, or PhD with 6+ years’ relevant experience or a Bachelor’s degree with 10+ years’ relevant experience, can be considered
Relevant experience includes: Strong track record with modern molecular design AI technologies and a demonstrated history of leadership and cross-disciplinary impact.
Deep proficiency in Python and PyTorch; experience training, fine-tuning and deploying large models on GPUs and HPC environments.
Experience with modern version control, CI/testing systems, and well-documented code practices.
Knowledge in at least two of: deep learning, diffusion models, reinforcement/active learning, LLMs in molecular design.
Demonstrated ability to translate computational work into experimental strategies and influence program decision-making.
Strong publication record or clear thought leadership in AI for biology/molecular design
Excellent communication, collaboration, and mentorship skills.
Detail oriented with strong documentation skills as demonstrated through examples from your GitHub repository or publications
Excellent written and oral communication skills; experience presenting technical results to diverse scientific audiences.
Demonstrated ability to generate valuable and relevant ideas, create concepts based on ideas, and develop new products based on concepts
Ability to set AI project metrics and drive activities to meet those metrics

Responsibilities

Provide senior scientific leadership: identify capability gaps, set goals, and lead initiatives that deliver business impact.
Lead research and development of generative AI methodologies for computational drug design; advance, optimize, and deploy models that balance multiple design criteria.
Translate computational insights into experimental strategies and leverage the organization’s substantial data-generation capabilities to train and validate models.
Develop and implement new deep learning approaches (e.g., diffusion models, reinforcement/active learning, LLMs for molecular design) and maintain a well-documented, reusable codebase with traceable model history.
Represent MolAI externally and internally: publish in top venues, present at conferences, and build collaborations with academic and commercial partners.
Mentor and grow talent: lead, guide, and develop junior ML scientists and engineers; promote best practices in version control, CI/testing, and model reproducibility.
Participate in cross-functional teams and program readouts, partnering closely with Digital Chemistry and Design, experimental scientists, research engineers, and IT.
Publish research in developing AI methods (example in ICLR, NeurIPS, ICML, Nature, Science, Cell etc.)
Advise leadership in the formation of global teams of experts to address specialized tasks
Drive the implementation of data science best practices across Novo Nordisk
Demonstrates ability to drive frequent collaborations with external commercial and academic partners.