AI ML Engineer

About the Role
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

• 3–6 years of experience in machine learning, spanning both classical ML and GenAI application work
• Strong 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