Senior Director, AI and Machine Learning– Evinova

On average, it takes more than 10 years to develop a drug and cost more than $1.3b. Over 70% of drug R&D cost is spending on clinical development and yet the success rate from phase I to approval is only around 10%.  At Evinova, a new health tech business as part of the AstraZeneca Group, we are under a mission to halve the cost and cycle time of clinical trials, by using state of the art AI and Machine Learning.  

If you are a solid coder with hands on experience of developing AI agentic solutions, good understanding of modern deep learning, strong AWS skills, and a voracious learner then you could be a fantastic fit for our team. Background in Biostatistics and Causal Inference will be a strong add on.

Talent with ambition to grow into a role will be a key differentiator of a successful candidate. Glass ceiling smashers especially welcome.

We are looking for a Senior Director of AI and Machine Learning to lead our AI and ML development. This role is a technical expert driving hands-on development from prototyping to production ready systems. The role will focus on solving complex clinical development challenge using AI and Machine Learning. From design of AI agents, communication architectures for agents, and developing automated techniques for designing and evaluating agentic systems, to traditional deep learning model (as well as Causal Machine Learning) development and deployment. The role will interact with product, design, engineering, MLops, and domain experts and partners.

On top of technical expertise, this role is also expected to hire and nurture a high performing team. When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office.

About the role:

This is a hands-on role with management responsibility, expect 50%-time spending on coding.

You will:

• Lead the design, development, and deployment of sophisticated agentic AI applications tailored to life sciences/health tech challenges.
• Develop automated techniques for designing and evaluating agentic systems
• Ideate, develop, and evaluate different tools for agents (e.g., search, memory, context compression, communication architectures for agents).
• Design specialized agent/LLM observability pipelines for prototypes and production systems.
• Develop bespoke deep learning models, from model design, training, testing all the way to deployment.
• Using causal machine learning for decision making.
• Hire, mentor and develop an AI team, fostering a culture of innovation and continuous learning, led by example with best ML and software engineering practice.
• Lead a portfolio of high-impact AI projects.
• Drive technical and project-level architecture decisions, guiding multi-functional teams through stages of the AI lifecycle.
• Deliver production ready code.
• Collaborate in a multidisciplinary environment to align AI initiatives with business objectives and drive digital transformation
• Represent the company's AI expertise at conferences, publications, and industry events.

Required Skills/Experience

• Ph.D. or equivalent experience in a relevant field (such as mathematics, computer science, data science, etc).
• 10+ years of proven experience in applied machine learning, with a strong focus on deep learning, NLP, and generative AI
• Proven track record of developing creative and novel AI solutions that have driven significant business impact.
• Extensive prior experience exploring and testing large language model behaviour, prompting and building products with language models.
• Expert knowledge of Python and advanced ML/LLM frameworks (e.g., TensorFlow, PyTorch, LangChain, LlamaIndex, etc).
• Deep understanding of agentic AI concepts and frameworks (e.g., agentic design patterns, multi-agent systems, reinforcement learning) and their applications in healthcare.
• Previous experience of training (fine turn) large language models, hands on experience with DeepSpeed  
• Extensive experience with AWS services (e.g., SageMaker, Bedrock, MSK, EKS, OpenSearch).
• Proven record of shipping production level code with best software engineering practice
• Experience with containerization technologies, CI/CD, front and backend of web applications
• Excellent verbal and written communication skills with experience presenting to executive leadership and partners.
• Demonstrated ability to lead and inspire multi-functional teams.
• Experience with TypeScript
• Experience with AWS CDK
• Demonstrated technical leadership experience, including successful delivery of large-scale AI projects.
• Experience designing and implementing novel AI architectures or algorithms in real-world products.

Desirable Skills/Experience

• Experience with low-level languages used for implementing high-performance ML code (C/C++, Rust, CUDA, etc.).
• Contributions to open-source AI projects or development of proprietary AI frameworks.
• Expertise in areas such as reinforcement learning, few-shot learning, meta-learning, Causal AI.
• Experience of Biostatistics

Knowledge of drug development and previously experience of working in pharmaceutical industrial is nice to have but not required.

Why Evinova?

Evinova draws on AstraZeneca’s deep experience developing novel therapeutics, informed by insights from thousands of patients and clinical researchers. Together, we can accelerate the delivery of life-changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment.  We know that regulators, healthcare professionals, and care teams at clinical trial sites do not want a fragmented approach. They do not want a future where every pharmaceutical company provides its own, different digital solutions. They want solutions that work across the sector, simplify their workload, and benefit patients broadly. By bringing our solutions to the wider healthcare community, we can help build more unified approaches to how we all develop and deploy digital technologies, better serving our teams, physicians, and ultimately patients.  Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI to serve the wider healthcare community and create new standards for the sector.  Join us on our journey of building a new kind of health tech business to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting-edge methods, and bringing unexpected teams together.

Interested? Come and join our journey.

So, what’s next?
Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.

Where can I find out more?

Our Social Media, Follow Evinova on LinkedIn https://www.linkedin.com/company/evinova/

Learn more about Evinova www.evinova.com

Date Posted

02-sep.-2025

Closing Date

21-sep.-2025

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

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 authorisation and employment eligibility verification requirements.