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Machine Learning Engineer

Spencer Rose LtdLondon🇬🇧United KingdomPosted 23 Jul 2026

Why This Role Stands Out

This hybrid Machine Learning Engineer role offers a compelling opportunity to build impactful AI solutions within a well-funded technology company, with a competitive salary of £110,000. You'll thrive here if you enjoy transforming cutting-edge research into scalable production software and collaborating with a multidisciplinary team to solve complex engineering challenges. Apply to contribute significantly to both technology and product development.

Quick Overview

Salary
£110k/yr
Work Type
Hybrid
Schedule
Full Time
Level
Mid Senior

Job Description

Machine Learning Engineer

London (Hybrid - 2 days per week) | Up to £110,000 + Benefits

Build AI that makes an impact in the real world.

We're partnering with an innovative, well-funded technology company that's applying advanced machine learning to solve complex, real-world engineering and optimisation challenges.

Following significant growth, they're looking for a Senior Machine Learning Engineer to help bridge the gap between cutting-edge research and production software. Working alongside Applied Scientists, you'll build the systems that enable machine learning models to be deployed, monitored and continuously improved in live environments.

If you enjoy turning research into scalable, production-ready software and want to work on genuinely challenging AI problems, this is an opportunity to have a significant influence on both the technology and the product.

The Role

You'll join a multidisciplinary engineering team responsible for taking machine learning models from experimentation through to production.

This is a hands-on software engineering role where you'll build the services, APIs and tooling that power the entire machine learning life cycle-from model training and deployment through to monitoring, automation and continuous improvement.

Working closely with Applied Scientists, you'll transform research prototypes into robust, maintainable production systems capable of operating reliably at scale.

What You'll Be Doing

  • Build and maintain Python applications that support the full machine learning life cycle
  • Develop APIs and services for model training, inference and evaluation
  • Deploy, version and manage machine learning models across production environments
  • Design monitoring and observability for production ML systems
  • Build automated workflows for model retraining, testing and deployment
  • Collaborate with Applied Scientists to productionise new machine learning models
  • Improve scalability, reliability and performance through automation and engineering best practice
  • Contribute to the design and evolution of the company's machine learning architecture

What You'll Bring

You'll have experience in several of the following:

  • Strong software engineering skills using Python
  • Experience building and deploying machine learning applications into production
  • Developing model serving, inference or training pipelines
  • Building REST APIs (FastAPI or similar)
  • Docker and containerisation
  • CI/CD pipelines
  • Linux
  • Production monitoring, logging and observability
  • Writing clean, maintainable and well-tested production code

Desirable Experience

Any exposure to the following would be beneficial:

  • MLflow, Weights & Biases or similar experiment tracking tools
  • Airflow, Prefect, Kubeflow or similar workflow orchestration platforms
  • Kubernetes
  • GPU-based workloads
  • Time-series or telemetry data
  • Distributed model training
  • Edge, on-premise or resource-constrained deployments
  • Industrial software, IoT or operational systems

Why Join?

  • Work on genuinely challenging machine learning problems with real-world impact
  • Collaborate closely with Applied Scientists and experienced software engineers
  • Influence the architecture and evolution of a growing AI platform
  • High levels of ownership and technical autonomy
  • Modern Python engineering environment
  • Backed by strong investment with ambitious growth plans
  • Hybrid working - 2 days per week in London
  • Salary up to £110,000

Skills

Docker
FastAPI
MLflow
Machine Learning
Airflow
IoT
Kubernetes
Python
REST

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