AI Scientist - AI Molecular Design
Danaher Corporation
Summary
The AI Scientist, Molecular Design is responsible for the development and deployment of ML/AI models that support molecular design initiatives across the organization. This position reports to the Director, AI & Data Science, Molecular Design. This position is part of the Danaher Enterprise AI team and will be fully remote.
Job description
In this role, you will have the opportunity to:
- Support ML/AI solution development by evaluating and applying algorithms, ML/AI tools and frameworks under guidance from senior team members.
- Collaborate with geographically distributed cross-functional teams to understand project requirements and assist in implementing ML/AI solutions that support molecular design efforts such as protein and binder design, mRNA optimization, antibody optimization, etc at various operating companies or across the enterprise.
- Drive data integrity and standardization across the assay-to-AI pipeline, ensuring high-quality datasets for model training and evaluation by coordinating assay scheduling, execution, data QC and reporting in partnership with experimental teams.
- Document workflows and findings to support knowledge sharing and integration of AI solutions into production environments.
- Engage in continuous learning by staying current with advancements in AI and machine learning relevant to molecular design.
The essential requirements of the job include:
- Master's degree or PhD in Computational Biology, Computer Science, Physics, Applied Math, or a related quantitative field with on-the-job experience in a relevant technical discipline.
- Hands-on coding and analysis experience with Python and machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, and RDKit.
- Demonstrated ability to develop, implement, test, and apply novel or adapted algorithms through original coding to address complex business problems, translating requirements into scalable and production-ready software solutions.
- Deep understanding of protein structure prediction and design algorithms, with demonstrated experience modifying, extending, or improving implementations of tools such as Chai-1, Boltz-2, BindCraft, BoltzGen, Mosaic, or Proteina Complexa.
- Experience with wet-lab validation methodologies for AI designs, including DMTA cycles and using wet-lab data to train AI models for hits optimization, particularly with methods used in antibody or VHH discovery.
It would be a plus if you also possess previous experience in:
- Experience working in life sciences, diagnostics, or biotechnology industries within cross-functional teams.
- Working proficiency with agentic frameworks such as LangChain or LangGraph and using large language models from Hugging Face, OpenAI or Anthropic APIs.
- Knowledge of NGS sequence analysis.
Requirements
- Master's degree or PhD in Computational Biology, Computer Science, Physics, Applied Math, or a related quantitative field
- On-the-job experience in a relevant technical discipline
- Hands-on coding and analysis experience with Python
- Experience with machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, and RDKit
- Demonstrated ability to develop, implement, test, and apply novel or adapted algorithms through original coding
- Ability to translate requirements into scalable and production-ready software solutions
- Deep understanding of protein structure prediction and design algorithms
- Experience modifying, extending, or improving implementations of tools such as Chai-1, Boltz-2, BindCraft, BoltzGen, Mosaic, or Proteina Complexa
- Experience with wet-lab validation methodologies for AI designs, including DMTA cycles
- Experience using wet-lab data to train AI models for hits optimization
- Experience with methods used in antibody or VHH discovery
- Experience working in life sciences, diagnostics, or biotechnology industries within cross-functional teams
- Working proficiency with agentic frameworks such as LangChain or LangGraph
- Experience using large language models from Hugging Face, OpenAI or Anthropic APIs
- Knowledge of NGS sequence analysis
Benefits
- Paid Time Off
- Medical Insurance
- Dental Insurance
- Vision Insurance
- 401(k)
- Bonus/Incentive Pay
- Remote Work
Company overview
Danaher Corporation is a leading global science and technology innovator headquartered in Washington, D.C., specializing in biotechnology, life sciences, and diagnostics. Founded in 1984 by brothers Steven and Mitchell Rales, the company has evolved from its origins as a manufacturing conglomerate into a premier healthcare technology organization with approximately 63,000 employees worldwide. Danaher operates through three core divisions: biotechnology (28% of revenues), which develops products for therapeutic development; life sciences (31% of revenues), focused on disease identification, new therapies, and drug testing/manufacturing; and diagnostics (41% of revenues), providing instruments, consumables, and software for disease diagnosis. The company's portfolio includes renowned brands such as Beckman Coulter, Cytiva, Pall Corporation, Cepheid, Leica Microsystems, and Abcam, serving pharmaceutical companies, biotechnology firms, healthcare providers, and research institutions globally. Danaher is distinguished by its Danaher Business System (DBS), a continuous improvement methodology that drives innovation and operational excellence. With 2024 revenues of $23.9 billion, the company ranks 180th on the Fortune 500 and plays a critical role in advancing scientific research, improving diagnostic capabilities, and accelerating the development of life-saving therapies.