What you will bring to the role:

• Designing, developing, implementing, training, testing, and refining modern deep learning AI models for data that is typically represented as sequences, such as text, graphs, or biological sequences (e.g., DNA, RNA, or proteins).
• Applying a deep understanding of foundation models, including pre-trained and large language models, to build generative AI applications in the domains of biology, chemistry, and text.
• Designing and developing innovative AI model architectures that leverage principles from encoder/decoders, jointly trained models, Siamese-twin models, VAEs, GANs, etc. You will also be involved in advanced training methods such as GPT and Diffusion, and developing/refining learning objectives including self-supervision.
• Taking a hands-on role and delivering on highly visible projects.
• Conducting applied AI experiments using scientific, rigorous, and reproducible methodologies on internal and public datasets to ensure publishable results.
• Serving as an ambassador for AI/Data Science by presenting and publishing articles.
• Building bridges between academia, technology, and industry partners.
• Keeping up-to-date with the latest developments in the field and mentoring associates.
• Being part of a unique organization and working with an interdisciplinary team of highly accomplished scientists to push the frontiers of AI in disease understanding and drug discovery.

Minimum Requirements:

• Master’s degree (PhD is highly desirable) in a computational field including, but not limited to: AI, Computer Science, Applied Mathematics, Computational Biology/Chemistry, Engineering, Statistics, and Physics
• 3 - 5 years of deep, hands-on experience working on AI projects with clear evidence of significant projects personally developed and delivered and/or publication track record 
• 3 - 5 years of experience in working with large scale, realistic data sets and analyzing results towards specific business/scientific outcomes
• Extensive experience with Large Language Models (LLMs), including prompt engineering, use of embeddings, RAG, LangChain, and application architectures using LLMs.
• Expert-level Python programming skills.
• Ability to work effectively in a team and elevate the team's performance in all aspects.
• Cloud computing optimization for high-performance AI model training.
• Experience in pharma, biotech, or healthcare is a big plus but not essential as a strong tech background with the willingness to adapt to pharma is acceptable.

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.