Associate Principal AI& ML Engineer – Evinova

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. You will 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.