At a Glance
- Tasks: Build AI engines to revolutionise drug development and enhance clinical trial success.
- Company: Join Evinova, a pioneering health-tech venture within AstraZeneca.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by developing cutting-edge AI solutions.
- Qualifications: Ph.D. or equivalent experience in relevant fields; strong coding skills required.
- Other info: Collaborative environment with a focus on innovation and meaningful outcomes.
The predicted salary is between 60000 - 84000 £ per year.
It currently takes over 10 years and $1.3B to develop a drug. More than 70% of that investment goes into clinical trials, yet only ~10% of candidates make it from Phase I to approval. Evinova - a new health-tech business within the AstraZeneca Group—is here to change the math. We use advanced algorithms and GenAI to aim high: boosting clinical trial success by 20%, cutting development time by 3 years, and halving study costs.
As Associate Principal AI&ML Engineer, you will build the AI engines that make those targets real—blending forecasting, optimization, and evidence synthesis to drive transparent and actionable recommendations. You’ll transform multi‑source data—historical signals, external context, and real‑world data (RWD)—into production‑grade intelligence and connect those insights into automated authoring and planning workflows, accelerating timelines, reducing cost, and raising the probability of success. If you are a solid coder with hands-on experience of developing AI agentic solutions, modern deep learning skills, strong AWS fundamentals, and a bias for rapid learning you can make a real impact here. This is a hands-on role, expect around 80% time spent on coding.
What the role involves:
- Build sophisticated GenAI applications, Machine Learning models, and Optimization solutions tailored to life sciences, taking them from initial PoC through to impactful applications.
- Deliver high‑quality, production‑ready code on AWS; stand up robust APIs, orchestration endpoints (MCPs), and flexible data pipelines with strong lineage and observability.
- Transform external signals and real‑world data (RWD) into trusted, actionable evidence for ML/DL and agentic systems.
- Collaborate in a dynamic ecosystem where AI, Product, Strategy, and UX intersect.
- Act as a key translator, connecting cutting-edge AI capabilities with real-world pharmaceutical requirements to deliver meaningful digital transformation.
- Communicate technical concepts and results clearly and effectively to technical and non-technical audiences.
- Keep pace with industry advancements by reviewing academic papers and attending conferences.
SKILLS AND CAPABILITIES NEEDED
- Ph.D. or equivalent experience in a relevant field (such as Mathematics, Computer Science, Machine Learning, Statistics etc).
- Previous demonstrated experience building applied ML/AI systems, including deep learning, NLP, and generative AI.
- Proven track record of developing creative and novel AI solutions with measurable business impact (e.g. cost, accuracy, adoption, latency).
- Knowledge of agentic design patterns (planning, memory, tool use/function calling, RAG) with evaluation, and guardrails.
- Proficiency in Python; PyTorch or TensorFlow; Hugging Face (Transformers/PEFT); experience with managed endpoints (OpenAI, Anthropic, AWS Bedrock) and at least one agent framework for tool orchestration.
- Ability to build secure, compliant ingestion and retrieval pipelines with provenance, hands-on experience with web automation, parsing, and document processing to enable high-quality RAG.
- Strong AWS fundamentals to deploy production workloads (model hosting, data, orchestration), including robust APIs/orchestration endpoints and observable data pipelines.
- Experience with containers and services (Docker, FastAPI, async patterns), CI/CD (GitHub Actions), and security/privacy-by-design suitable for regulated environments.
- Comfortable leveraging GenAI coding assistants (GitHub Copilot, Cursor, etc.) to accelerate development.
NICE TO HAVE
- Experience with real-world data (Electronic Health Records, claims data, pharmacy & prescription databases).
- Knowledge of drug development and prior pharma experience.
- Reinforcement learning and LM fine-tuning; TypeScript or AWS CDK.
- Contributions to open-source or internal frameworks.
Why Evinova (AstraZeneca)?
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.
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.
Associate Principal AI& ML Engineer – Evinova in London employer: AstraZeneca GmbH
Contact Detail:
AstraZeneca GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Principal AI& ML Engineer – Evinova in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Evinova or AstraZeneca. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your best projects, especially those related to AI and ML. When you get the chance, share your work during interviews to demonstrate your expertise.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by solving coding challenges and brushing up on your deep learning knowledge. The more prepared you are, the more confident you'll feel.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of our mission at Evinova.
We think you need these skills to ace Associate Principal AI& ML Engineer – Evinova in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your coding skills and experience with AI and ML in your application. We want to see how you've tackled real-world problems using your expertise, so don’t hold back on showcasing your projects!
Tailor Your Application: Take a moment to customise your application for the Associate Principal AI&ML Engineer role. Use keywords from the job description and relate your experiences directly to what we’re looking for. It shows us you’re genuinely interested!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that communicate your ideas effectively, especially since you'll need to do this in the role too!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to navigate!
How to prepare for a job interview at AstraZeneca GmbH
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, PyTorch, and AWS. Brush up on your deep learning and generative AI skills, as you'll likely be asked to discuss your hands-on experience with these tools.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've tackled complex problems in AI and ML. Think about projects where you’ve built applied ML systems or developed creative AI solutions that had a measurable impact. Be ready to explain your thought process clearly.
✨Communicate Like a Pro
Since you’ll need to connect technical concepts with non-technical audiences, practice explaining your work in simple terms. Use analogies or real-world examples to make your points relatable. This will show your ability to bridge the gap between tech and business needs.
✨Stay Current with Industry Trends
Familiarise yourself with the latest advancements in AI and ML, especially in the context of healthcare. Mention any recent papers you’ve read or conferences you’ve attended. This shows your passion for the field and your commitment to continuous learning.