Machine Learning Engineer

Norton Blake; City Of London; Hybrid; GBP 80,000 - 110,000; Full time

Job summary

A technology solutions company in London is seeking a Machine Learning Engineer. The candidate will design and implement ML/NLP models, improve data pipelines, and collaborate with the team while working in a hybrid model. The ideal candidate has strong experience with Python, cloud deployment, and NLP techniques, alongside a passion for MLOps best practices.

Qualifications

• Strong experience working with textual data and NLP.
• Proven ability to write clean, testable Python code.
• Hands-on experience with ML/DL frameworks like PyTorch and TensorFlow.

Responsibilities

• Design, build, and productionise ML/NLP models for SaaS products.
• Improve performance and scalability of data ingestion and pipelines.
• Collaborate through code reviews and knowledge sharing.

Skills

Experience with textual data and NLP

Clean, testable Python code

Familiarity with SQL

Hands-on experience with ML/DL frameworks

End-to-end cloud deployment

Strong maths/stats grounding

Tools

PyTorch

TensorFlow

Hugging Face

Job description

Overview

Machine Learning Engineer, ML Engineer, Hybrid, up to 110k
London (Hybrid - 5 days a month)
£80,000 - £110,000 depending on experience

What You'll Do

• Design, build, and productionise ML/NLP models for large-scale SaaS products and APIs


• Write clear, modular, testable Python code and deploy via modern CI/CD pipelines


• Improve performance and scalability of models, data ingestion, cleaning, and pipelines


• Explore new ML/NLP techniques and keep the team up to date with research trends


• Propose cloud architectures and ensure robust ML operations (MLOps)


• Collaborate through code reviews, knowledge sharing, and documentation

What We're Looking For

• Strong experience working with textual data and NLP


• Proven ability to write clean, testable Python code


• Familiarity with SQL and NoSQL/graph databases


• Hands-on experience with ML/DL frameworks (e.g. PyTorch, TensorFlow, Hugging Face)


• End-to-end cloud deployment experience (AWS, GCP, or Azure)


• Solid grasp of data structures, modelling, and cloud-based architecture


• A systems thinker with a passion for MLOps best practices


• Strong maths/stats grounding and ability to collaborate with research-oriented colleagues

Please apply for more information