We are looking for a Machine Learning Engineer with a strong foundation in classical machine learning who has since moved into building applications powered by Generative AI. The ideal candidate brings hands-on experience working on problems in the pharmaceutical or life sciences domain.
Key Responsibilities :
- Design and deploy machine learning models using classical techniques such as regression, tree-based methods, and ensemble models.
- Build and productionize GenAI applications, including LLM-based tools, retrieval-augmented generation (RAG) systems, and document intelligence pipelines.
- Work with structured and unstructured pharma data such as clinical, regulatory, or scientific datasets.
- Adapt and evaluate LLMs for domain-specific use cases.
- Collaborate with domain experts to translate business requirements into ML/AI solutions.
- Own the ML lifecycle from data preparation through deployment and monitoring, while being mindful of data privacy and compliance in pharma contexts.
Required Skills &
Experience :
- 36 years of experience in machine learning, spanning both classical ML and GenAI application work.
- Robust Python skills and experience with standard ML/deep learning frameworks.
- Practical experience with LLM tooling, prompt engineering, and RAG-based architectures.
- Experience working with pharma, healthcare, or life sciences data.
- Familiarity with cloud platforms and MLOps practices.