Production ML Engineer — Cloud-Native & MLOps

Anson McCade; Greater London; Hybrid; GBP 144,000 - 176,000; Full time

Job summary

Anson McCade is seeking a talented Machine Learning Engineer in London to deliver production-grade AI solutions. Join a high-performing team working across software, ML, and cloud technologies to build scalable platforms with tangible impact.

You will design, deploy, and operationalise ML models, collaborate with engineers and data scientists, and drive architecture decisions while applying MLOps practices across AWS, Azure or GCP environments.

Qualifications

• 4+ years' commercial experience as a Machine Learning Engineer.
• Proven track record of deploying and operationalising machine learning models in production environments.
• Excellent Python development skills and solid software engineering principles.
• Experience with PyTorch, TensorFlow, or Scikit-learn.
• Strong knowledge of cloud platforms including AWS, Azure, or GCP.
• Hands-on experience with Docker, Kubernetes, and modern DevOps/MLOps practices.
• Understanding of machine learning fundamentals, statistics, and model evaluation techniques.
• Strong stakeholder management and communication skills.

Responsibilities

• Design, build and deploy production-grade ML applications and infrastructure.
• Develop scalable, reusable software components for AI and data-driven solutions.
• Collaborate with software engineers, data scientists, product teams, and stakeholders to deliver high-impact projects.
• Lead technical design discussions and contribute to architecture decisions for complex ML systems.
• Build and maintain cloud-native solutions across AWS, Azure or GCP environments.
• Implement best practices around MLOps, deployment, monitoring, security, and scalability.
• Translate complex technical concepts into clear recommendations for technical and non-technical audiences.

Skills

Python

MLOps

Communication

Tools

Docker

Kubernetes

Job description

Anson McCade is seeking a talented Machine Learning Engineer in London to deliver production-grade AI solutions. Join a high-performing team working across software, ML, and cloud technologies to build scalable platforms with tangible impact.

You will design, deploy, and operationalise ML models, collaborate with engineers and data scientists, and drive architecture decisions while applying MLOps practices across AWS, Azure or GCP environments.