ML Engineer - Production AI for Healthcare Scheduling

Lantum; City Of London; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A leading UK healthcare technology company is seeking to enhance its AI scheduling engine. The role involves building and optimizing production-grade AI models, improving data pipelines, and collaborating closely with engineering teams. The ideal candidate will have strong data science skills and a deep understanding of Python and machine learning frameworks. This position promotes a vibrant hybrid working environment with a focus on innovation and team collaboration.

Benefits

Home office set up stipend

Health Cash Plan

Pension matching 4%

25 days holiday + birthday leave

Wellbeing support

Learning and development budget

Cycle to Work Scheme

Charity Day

Qualifications

• Strong end-to-end data science skills with experience deploying models into production.
• Deep expertise in Python, ML frameworks, optimization methods, and cloud engineering.
• Ability to work with messy real-world data and design robust solutions.

Responsibilities

• Build, optimize, and maintain production-grade AI models for complex rota scheduling.
• Improve data pipelines and workflows to enhance model reliability.
• Collaborate with engineering to embed AI into core product workflows.

Skills

End-to-end data science skills

Expertise in Python

ML frameworks

Cloud engineering

Attention to accuracy

Education

Degree in mathematics, statistics, physics, computer science, engineering or a STEM field

Tools

Python data science stack (Pandas, NumPy, etc.)

ML frameworks (PyTorch, Keras)

Cloud services (AWS)

Data visualization tools (Matplotlib)

CI/CD

Git

Job description

A leading UK healthcare technology company is seeking to enhance its AI scheduling engine. The role involves building and optimizing production-grade AI models, improving data pipelines, and collaborating closely with engineering teams. The ideal candidate will have strong data science skills and a deep understanding of Python and machine learning frameworks. This position promotes a vibrant hybrid working environment with a focus on innovation and team collaboration.