Principal Scientist, Generative AI
About the team
Predictive AI and Data teamis responsible forproviding AI and Bioinformatics solutions to the scientists across the spectrum of drug development and discovery in AstraZeneca (both pre-clinical and clinical stages). The primary aim is to find ways to accelerate the drug development process byleveragingexisting company data in combination with the mostcutting-edgeAI approaches in day-to-day scientific work across the company.
Introduction to role
Thishands-onrole issimilar toaforward deployed engineer (FDE)and willwork directly with customersacross the spectrum of drug developmentpipelineto configure and implementgenerative AIsolutions(including Large Language Models, other Foundation Models and Agentic AI workflows)to demonstrate value to the business in accelerating existing scientificprocesses.You will then help build out the robust solution in production in collaboration with other data science and software developer teams.In particular,usingagentic AI workflows to integrate different analysis steps across bioinformatic and machine learning workflowswill be a major focus and will include working with machine vision, transcriptomics, and language foundation models.
Accountabilities
- Collaborate withscientistsfrom across the company to understand their challenges and work with them to build the platform that underpins their research.
- Build generative AIprototype solutions todemonstratevalue in accelerating routine scientific processes.
- Take responsibility for designing, and deploying machine learning models for a large-scale analysis of clinical transcriptomics, proteomics, and cell paintingdata
-CalculateROIandimpactfor AI projects obtaining necessary information and assumptions from stakeholders and future users
- Provide strategic direction and leadership for the organisation as well as collaborate with senior leadership to define and implement the generative AI strategy, finding opportunities for generative AI adoption and driving business impact.
- Champion a “production first attitude” to ensure the necessary infrastructure and platforms are available to scale exploratory research to production.
- Build and manage effective relationships with stakeholders to ensureutilizationand value of information resources and services. Clearly and objectively communicate results, as well as their associated uncertainties and limitations to shape solutions
- Be a part of a hard-working team, continuously improving AstraZeneca’s Machine Learning development environments, platforms, and tooling.
- Work effectively across severaltimezoneswith AI research teams in China, India,Europeand the US East Coast, communicating the requirements for the AI models and evaluating the available solutions
- Work closely and collaboratively with internal governance and compliance functions such asCyber Security and Data Privacy to securethe computing environmentwithout obstructing end-user productivity.
Essential Skills/Experience
-Bachelor’sdegree, orMaster’s (or equivalent years of experience) in mathematics, computer science, engineering, physics, statistics, computationalsciencesor a related field.
- Advanced skills in programming languages such as Python, and experience with AI libraries and frameworks (e.g., TensorFlow,PyTorch).
- Proven experience in AI and machine learning,in areas such asdeep learning, natural language processing, computer vision, and reinforcement learning.
- Experience in prompt engineering, implementing Retrieval-Augmented Generation (RAG), and LLM fine-tuning
-Demonstratedexperience in implementing generative AI workflows (large language models, other foundationmodelsor agentic frameworks) to automate existing process or enable new ones, ideally in the Pharma and/or Healthcare space
- Experience of manipulating and analysing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across stakeholders
- Experience designing agentic AI workflows and an ability to plan strategically for the AI needs in a large organisation
- Strong knowledge of software developmentand machine learning deploymentprinciples
- Familiarity with existing machine vision models: CNNs, vision transformers, diffusion models etc. for self-supervised and multimodal training (e.g.,ResNet,UNet, DINO, CLIP, Stable Diffusion)
- Advanced skills in programming languages such as Python, and experience with AI libraries and frameworks (e.g., TensorFlow,PyTorch).
- Familiarity with GitHub,CI/CD pipeline, and best DevOps andMLOpspractices
- Demonstratable experience working with AWS or a similar cloud environment
- Experience working with Kubernetes and/or container-based application deployments.
- Excellent communication and presentation skills, with the ability to convey complex AI concepts to non-technical partners.
- Strong leadership and project management skills, witha track recordof leading successful AI projects
- Knowledge of AI ethics and responsible AI practices
Desirable Skills/Experience
- Experience in life sciences,healthcare, or pharmaceutical industry.
- Experience in a complex global organization.
- Experience using DevOpsandMLOpsto enable automation strategies
- Experience with LLM frameworks (LangChain,AutoGen,LlamaIndex)
- Experience working in an Agile team with knowledge or experience of working in product or platform-focused delivery
- Familiarity with modern foundation models for transcriptomics or Cell Painting data(e.g.,Geneformer,scGPT,scFoundationetc.)
- Track record of publications in top AI conferences or journals in pharmaceutical research (e.g.,NeurIPS, ICML, Nature Machine Intelligence, Nature Communications, NEJM AI, etc.)
Date Posted
17-8月-2026Closing Date
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.