Lead AI Scientist

The Lead AI Scientist must understand AI algorithms at a scientific level, including their development, progression, and interaction with data. The Lead AI Scientist must be highly proficient in Python and capable of performing hands-on technical work rather than operating primarily as a people manager. Candidates should have held at least a senior or lead position, although a technically hands-on director from a startup could also be considered. The role may mentor junior AI engineers and scientists but will not have direct reports.

In DHR Enterprise AI Solutions, you will be responsible for exploring and validating emerging AI methods, designing rigorous evaluations and turning promising research into practical capabilities that Danaher can industrialize and scale. This hybrid role will require working occasionally in our Boston facility.

In this role, you will have the opportunity to:

• Identify and investigate emerging AI methods with potential to address high-value scientific, operational or commercial challenges across Danaher.
• Design rigorous experiments, benchmarks and evaluation approaches that make capability, limitations and risk transparent.
• Develop and test novel modelling, reasoning, retrieval or agentic approaches in partnership with AI and software engineers.
• Translate research findings into clear recommendations, reusable methods and production-minded prototypes for wider adoption.
• Communicate complex scientific concepts to technical and business audiences and mentor colleagues in advanced AI practices.

The essential requirements of the job include:

• Minimum master's degree, with a PhD preferred. Relevant disciplines include artificial intelligence, data science, machine learning, computer science, mathematics, physics, or a related subject. Candidates without a PhD should have approximately five years of experience following completion of a master's degree. PhD work may satisfy the experience expectation.
• Strong expertise in machine learning, generative AI, statistical methods and experimental design.
• Ability to move from literature and emerging research to reproducible experiments and practical enterprise applications.
• Hands-on proficiency with Python, modern AI frameworks, evaluation methods and relevant cloud or compute environments.
• Sound scientific judgement, intellectual curiosity and the ability to challenge assumptions with evidence.
• Excellent written and verbal communication skills across research, engineering and business audiences.
• Ability to travel up to 10% domestically and internationally, as needed, to support program delivery, business engagement, partner coordination, audits, training, or operational readiness.

It would be a plus if you also possess previous experience in:

• Applied AI research or advanced model-development programs.
• Designing model, agent or system evaluation frameworks.
• Transferring research innovations into enterprise products or production solutions.