Job Description

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  

You'll have the opportunity to work on a mixture of the following:

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:

We are looking for professionals with these required skills to achieve our goals:

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:

If you have the following characteristics, it would be a plus:

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: Thursday 31st July 2025 (COB)

Please take a copy of the Job Description, as this will not be available post closure of the advert. 
When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.

During the course of your application, you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process.  If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements, please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.

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