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# Machine Learning Engineer

- **Company:** Anson McCade
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £100,000.0 - £140,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Pytorch, Large Language Models, Deep Learning, Generative AI, Kubernetes, Deployment Automation, Machine Learning Operations, Docker
- **Published:** August 9, 2026
- **Apply:** https://www.totaljobs.com/job/machine-learning-engineer/anson-mccade-job107811178

## About the Role

We're interested in engineers with strong commercial experience across Machine Learning and software engineering, particularly those who have taken models from development through to production.

Experience with areas such as:

 * Python and modern software engineering practices
 * Machine Learning / Deep Learning
 * MLOps and production ML systems
 * Cloud platforms and scalable infrastructure
 * ML frameworks such as PyTorch, TensorFlow or equivalent
 * LLMs / Generative AI is highly desirable
 * CI/CD, Docker, Kubernetes or similar technologies
 * Designing and operating production-scale ML platforms

For Lead and Principal positions, we're particularly interested in engineers who can demonstrate technical leadership, architectural ownership and the ability to influence engineering direction.

## Description

As a Machine Learning Engineer, you will work across the full ML lifecycle, from designing and developing models through to deploying, scaling and continuously improving production systems.

Depending on seniority, you will also have the opportunity to take ownership of technical direction, mentor engineers and shape how Machine Learning solutions are architected and delivered., * Develop and deploy production-grade Machine Learning solutions, building scalable AI systems that solve complex real-world challenges.

 * Design end-to-end ML architectures, including model development, MLOps pipelines, deployment strategies and continuous optimisation.
 * Collaborate with engineering, data and product teams to deliver robust, production-ready AI solutions using modern ML and software engineering practices.
 * Provide technical leadership and mentorship, with Lead and Principal Engineers influencing architecture, engineering standards and the wider technical direction of projects.


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- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning)
- [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning)

## Related Articles

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- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
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