Senior Lead ML Scientist - Molecular AI

Role Summary

Senior Lead/Principal ML Scientist – Molecular AI is a senior, high-impact role within MolAI. You will set scientific and technical direction for the team, develop AI-driven projects that influence R&D priorities, and serve as a technical champion for generative AI in molecular design. You will mentor colleagues, drive cross-functional initiatives, and translate computational insights into experimental strategies to accelerate therapeutic discovery.

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 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 (e.g., ICLR, NeurIPS, ICML, Nature, Science, Cell).
• Advise leadership in forming global teams of experts to address specialized tasks.
• Drive the implementation of data science best practices across the organization.
• Demonstrate ability to drive frequent collaborations with external commercial and academic partners.

Qualifications

• Required: Bachelor’s degree in machine learning, computer science, computational chemistry, or a related quantitative discipline; Master’s or PhD highly preferred.
• Required: Relevant experience including a strong track record with modern molecular design AI technologies and leadership impact.
• Required: Deep proficiency in Python and PyTorch; experience training, fine-tuning, and deploying large models on GPUs and HPC environments.
• Required: Experience with modern version control, CI/testing systems, and well-documented code practices.
• Required: Knowledge in at least two of: deep learning, diffusion models, reinforcement/active learning, LLMs in molecular design.
• Required: Demonstrated ability to translate computational work into experimental strategies and influence program decision-making.
• Required: Strong publication record or clear thought leadership in AI for biology/molecular design.
• Required: Excellent communication, collaboration, and mentorship skills; detail-oriented with strong documentation skills.
• Required: Excellent written and oral communication skills; ability to present technical results to diverse scientific audiences.
• Required: Ability to set AI project metrics and drive activities to meet those metrics.

Education

• Bachelor’s degree in machine learning, computer science, computational chemistry, or related quantitative discipline required; Master’s degree or PhD highly preferred.

Skills

• Python
• PyTorch
• Large-model training, fine-tuning, and deployment on GPUs/HPC
• Diffusion models, reinforcement/active learning, LLMs in molecular design
• Version control, CI/testing, and reproducible research practices
• Scientific communication and collaboration across multidisciplinary teams

Additional Requirements

• Up to 10% overnight travel required, including internationally