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Research AI Engineer

Danaher

Bangalore, Karnataka, India

Applied AI

Posted 3 hours ago

midonsite

Verified open on Oct 13, 2026 · posted today

Job Description

Bring more to life.


Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology?


At Cytiva, one of Danaher’s 15+ operating companies, our work saves lives—and we’re all united by a shared commitment to innovate for tangible impact. 


You’ll thrive in a culture of belonging where you and your unique viewpoint matter. And by harnessing Danaher’s system of continuous improvement, you help turn ideas into impact – innovating at the speed of life.


Working at Cytiva means being at the forefront of providing new solutions to transform human health. Our incredible customers undertake life-saving activities ranging from fundamental biological research to developing innovative vaccines, new medicines, and cell and gene therapies.


At Cytiva you will be able to continuously improve yourself and us – working on challenges that truly matter with people that care for each other, our customers, and their patients. Take your next step to an altogether life-changing career.


Learn about the Danaher Business System which makes everything possible.


As a Research AI Engineer you are responsible for developing AI-driven solutions that combine classical statistical modelling, machine learning and modern generative AI techniques to solve complex business and scientific challenges. Your work will enable smarter bioprocess control, predictive insights, and optimization strategies, accelerating the development of life-saving therapeutics.


This position reports to the Senior Research Manager and is part of the Central Technology Organization (CTO) R&D department located in Bangalore and will be an on-site role.  


What you will do:

  • Work closely with scientists, engineers, and product teams to translate ideas into impactful solutions by applying statistical analysis, ML and AI techniques.
  • Perform exploratory data analysis, feature engineering, model development, validation, and performance assessment, on structured and unstructured data.
  • Design and develop Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), tool calling, and multi-agent workflows while applying strong analytical and data science principles to extract insights, build predictive models, and drive decision-making
  • Build data pipelines, integrate with enterprise systems, databases, APIs, and deploy AI/ML solutions on cloud platforms such as AWS and Azure.
  • Stay current with advances in ML / AI / Gen AI / Agentic AI areas, and contribute to reusable AI assets, best practices, and technical standards methodologies.

Who you are:

  • Master’s degree in Data Science, Artificial Intelligence, Chemical Engineering, Bioprocess Engineering or related fields
  • 4+ years of experience in Data Science, Machine Learning, Applied AI
  • Strong proficiency in Python and common data science libraries such as Pandas, NumPy, Scikit-learn, and related tools.
  • Experience with Large Language Models (LLMs), prompt engineering, RAG, embeddings, and Agentic AI frameworks.
  • Familiarity with LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar technologies.

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

  • Bioprocessing or life sciences
  • AWS or Azure AI/ML services, MLOps, CI/CD, Docker, model deployment, and monitoring

Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

For more information, visit www.danaher.com.

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Career context

This role is classified as Applied AI.

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$198k - $256k is the middle 50% of disclosed salaries, measured from 425 live Applied AI postings on this board. Roughly two thirds of postings disclose nothing, so this describes the ones that do, not the whole market.

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