AI/ML Python Engineer

Experis

London, UK

23 days ago

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Role details

Contract type

Permanent contract

Employment type

Part-time (≤ 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.experis.co.uk

Tech stack

Artificial Intelligence Language Modeling Backend Fastapi Terraform Docker

Job description

Imagine building advanced software that helps develop novel therapies-and adapts quickly as diseases emerge and change. Our Client is hiring a Software Engineer to join its AI/ML team, where ownership, collaboration and continuous development aren’t just values on paper-they’re how you’ll work day to day.

What you’ll be doing:

Build and improve the back end of a Python web application that supports AI/ML-driven solutions
Define, deploy and manage infrastructure within a cloud environment
Integrate AI/ML components with frontend, data, and compute infrastructure to create end-to-end value
Write quality, well-documented, well-tested software-supported by automated test suites
Develop, measure and monitor key metrics for tools and services, then iterate to improve performance and reliability
Take part in code reviews and raise engineering standards across the team
Collaborate with data engineers and other technical teams to build an end-to-end pipeline consuming data products

Requirements

Strong Python skills, with a track record of shipping quality production code
Experience with unit testing (e.g. pytest) and a mindset of building for reliability
Confidence working with cloud-native systems and deploying to cloud platforms for real user populations
Practical experience with infrastructure as code (e.g. Terraform)
Comfort working in agile environments and following modern, disciplined development practices (e.g. git/GitHub)
A continuous learning approach-staying curious, iterating, and improving your craft over time
Passion for solving problems that can support new and existing therapies

Additional information:

Experience with Python backend frameworks such as FastAPI is a plus
Background or exposure to biological/scientific data (e.g. genomics, transcriptomics, proteomics) or pharmaceutical work is beneficial
Knowledge of AI/ML deployment-especially language models, NLP or agent-based approaches-is a strong advantage
Experience with Docker/containerised applications (including multi-container architecture) is desirable
Mentoring/coaching and technical leadership experience is strongly valued