Senior Principal AI/ML Engineer

GSK is a global leader in pharmaceuticals and healthcare, with a relentless commitment to advancing healthcare for the betterment of humanity. Our mission is to help people around the world do more, feel better, and live longer. We achieve this by researching, developing, and providing innovative medicines and vaccines. Our dedication to scientific excellence and ethical practices guides everything we do.

R&D at GSK is highly data-driven, and we're applying AI/ML and data engineering to generate new insights, enable analytics, gain efficiencies and automation.

This role is based in an AI/ML team that is already working on projects involving Generative AI, Information Retrieval, NLP/NER/RE, document classification, and has won awards and recognition for its work. The team's future projects will be in diverse areas, such as regulatory, clinical, legal and HR. Versatility is key, with an ability to quickly understand domain data and requirements and translate them into solutions. You will interact with architects, software and data engineers, modelers, product owners as well as other team members in Clinical Solutions and R&D. You will actively participate in creating technical solutions, designs, implementations and participate in the relentless improvement of R&D Tech systems in alignment with agile and DevOps principles.

We're looking for demonstratable expertise across a selection of the following key competencies: Generative AI, model building, training and evaluation, natural language processing, classification problems, data engineering, and software development. You should also be versed in agile ways of working, source control and the Azure cloud.

In this role you will

• Generative AI
  • Design and develop RAG based applications
  • LLM fine-tuning, including preparation of training sets from internal data
  • Agent-based applications
  • Evaluating use-case specific LLMs
• AI/ML Engineering
  • NLP: Named Entity Recognition across a variety of unstructured data
  • Evaluating and training BERT-like models such as GLiNER, NuNER for NER tasks
  • Analysing trade-offs between these models and LLMs for NLP tasks
  • Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG
  • Document and text Classification
• Data Engineering
  • Designing and implementing data pipelines for model training and inference
  • Building scalable data processing systems
  • Optimizing data workflows and storage solutions
  • Implementing robust ETL processes
  • Evaluate and integrate new technologies and models
• Cross-team collaboration, identifying innovations and architecting solutions
• Provide leadership and technical direction to various business units and partners

Why you?

Qualifications & Skills:

• Bachelor's degree in computer science
• Significant experience working in AI/ML and Python
• Strong Python programming skills with demonstrated expertise in building production-grade applications
• Generative AI: Demonstratable experience of RAG, including chunking strategies, vectorising and indexing data, retrieval strategies and reranking, prompting strategies, function calling. Our current tech-stack is OpenAI, LangChain, Azure AI, Python, pg_vector, Sinequa.
• AI/ML: Hands on experience with training and evaluating BERT-like models in real-world applications, especially in NLP or classification problems
• Data Engineering: Experience with data pipeline development, ETL processes, and working with large datasets
• Hands on experience with ML tools like TensorFlow, PyTorch etc.
• Experience with Azure cloud (AKS, Azure AI, ADF, Document Intelligence etc.)
• Excellent problem-solving skills and software engineering practices
• Excellent communication skills

Preferred Qualifications & Skills:

• Master's or PhD in Computer Science
• Generative AI: Experience of multi-agent systems (LangGraph, Autogen, CrewAI etc.) would be a plus, as would experience of multimodal LLMs (like GPT4 Omni, Qwen-vl, DocOwl etc.) for understanding complex documents and images. Experience in training, evaluating and hosting open source LLMs would be a major benefit.
• Some experience with MLOps would be very beneficial
• Full-stack development experience
• Experience with UI technologies like React would be helpful
• Experience with building search applications using Azure Search, Sinequa, Elastic or anything Lucene-based would be beneficial
• Familiarity with containerization technologies (Docker, Kubernetes)

Closing Date for Applications

Wednesday 29th October 2025 (COB)

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases - to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.