Lead ML Engineer, Digital Drug Discovery

APPLY HERE: Lead ML Engineer, Digital Drug Discovery

Location: London, United Kingdom

permanent, full-time job

Hybrid working model, with at least 2-3 days from the office

For over 100 years we have been driving change to defeat diabetes, but we know that what got us here today is not necessarily what will make us successful in the future. We are now transforming our business and taking our expertise into new territories including obesity and rare blood and endocrine diseases.

Our story is one of incredible growth and success, which has culminated in receiving many prestigious awards, such as Best Places to Work and Vitality – Britain’s Healthiest Workplace.

The Position

The Digital, Data and IT, Research and Early Development (DD&IT-R&ED) team is on the lookout for a passionate and innovative Lead AI/ML Engineer with solid expertise in deploying LLM models into production.

This role is pivotal in optimizing and deploying AI/ML solutions that drive the future of drug development. You will work with a state-of-the-art GenAI application with multi-agent workflow that helps with the drug discovery portfolio management. It’s an opportunity to revolutionize ML in the pharmaceutical industry and collaborate with a diverse, strong and upbeat cross-functional team.

Your key responsibilities will include:

• Collaborative Innovation: working directly with AI/ML scientists on optimization and production deployment of solutions, creating blueprints, and acting as an internal consultant to transition ideas from prototype to production.
• Data Exploration & Visualization: Exploring and visualizing data to understand those and identify differences in data distribution that could affect model performance when deployed in real-world scenarios.
• Data Quality Assurance: Verifying data quality and ensuring it through data cleaning and ML validation strategies.
• Scalable Solutions: Building training pipelines and components to ensure scalable ML solutions, address errors, and provide education to upskill teams working on ML, enhancing MLOps proficiency.

We offer a flexible hybrid working model with 2 days from home and 2-3 days at our central London office, where you'll collaborate with digital specialists and scientists. We prioritise work-life balance and foster a supportive, inclusive culture where your contributions are valued.

Qualifications

We are looking for a candidate with a positive personality, effective communication skills and well-established technical leadership expertise who values a collaborative environment. You should have experience working with technical data scientists, data engineers, and life scientists. A PhD or master's degree with relevant experience, or a bachelor's degree with solid expertise, is required. Recent work experience in a healthcare/life science organization is considered an asset.

Other skills we are searching for are:

• Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer.
• GPU Computing: Familiarity with GPU computing, both on-premises and on cloud platforms, and experience in building end-to-end scalable ML infrastructure with on-premise DGX or cloud platforms including AWS EKS/SageMaker, Azure Machine Learning/AKS, or common ML platforms (ClearML, MLflow, Weights and Biases).
• Cloud & Automation: Strong understanding of AWS, Azure, containerization/Kubernetes, multiple automation/DevOps, and ML lifecycle practices.
• Data Handling: Practical knowledge in data wrangling, handling, processing, integrating, and analyzing large heterogeneous data sets related to drug discovery.
• LLM Experience: Experience with LLMs (fine-tuning, pretraining, continued pretraining, inference, RAG, and building multi-agent workflows using Llamaindex, Langchain, LangGraph, vector databases, etc.).
• Production-Grade Models: Significant expertise in building production-grade machine learning models in industry and/or academic research settings, building, training, and deploying ML.

About the Department

The position is connected to our DDIT-R&ED UK department located in the heart of London and the University of Oxford medical campus. The department currently consists of 13 Software-, Cloud-, and ML-Engineers and is building up additional capabilities and capacity.

We are strongly linked with the Novo Nordisk Research Centre Oxford (NNRCO), an innovative target discovery unit with a focus on identifying novel, game-changing therapies for patients. The site is a fusion of the best of academia, biotech, software engineering, and big pharma to realize cutting-edge biology. NNRCO operates at the boundaries of frontier science with a mandate to find dynamic, agile, and distinctive new ways of working to diversify the company’s pipeline with disruptive medicines. We strive to efficiently drive digital, data & IT innovation and transformation by leveraging agile methodologies.

Working at Novo Nordisk

We are a proud life-science company, and life is our reason to exist. We’re inspired by life in all its forms and shapes, ups and downs, opportunities and challenges. For employees at Novo Nordisk, life means many things – from the building blocks of life that form the basis of ground-breaking scientific research, to our rich personal lives that motivate and energise us to perform our best at work. Ultimately, life is why we’re all here - to ensure that people can lead a life independent of chronic disease.