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 Senior AI/ML Engineer. This role is pivotal in optimizing and deploying AI/ML solutions that drive the future of drug development. If you’re excited about revolutionizing AI/ML in the pharmaceutical industry and collaborating with a diverse team of AI/ML scientists, scaling up exploratory work, and transitioning solutions from notebooks to robust ML pipelines, this could be your next career move.
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 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 analysing large heterogeneous data sets related to drug discovery. LLM Experience: Experience with LLMs (refining, DPO, training, hosting, RAGs, and working with multiple agents including LaMDA index, 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 14 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.