MLOps Engineer

MLOps Engineer

London Based - Hybrid (Three days per week on site)£90,000 to £110,000 plus bonus

This is an exciting opportunity to join a mission driven cleantech scale up as they continue to grow their data and AI function. You will help shape a modern MLOps environment, working on impactful machine learning deployments that directly support smarter, cleaner energy systems.

The Company

They are a fast growing technology scale up within the energy and electric space. The team is collaborative, customer focused, and driven by a strong product mindset. You would be joining a small, high impact data group with experienced engineers and the opportunity to take real ownership.

The Role

In this MLOps Engineer role, you will contribute to the design, deployment and optimisation of production ML systems.

Responsibilities include:

• Supporting data scientists and AI engineers to build, deploy and monitor ML models in production environments.
• Managing ML lifecycle
• Designing scalable ML pipelines for training, validation and deployment.
• Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints.
• Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure.
• Applying strong engineering standards across cloud, DevOps and automation practices.
• Contributing to computer vision and broader ML workloads, with scope to support new AI initiatives as they grow.

Your Skills and Experience

To succeed, you will bring strong commercial experience in:

• Python and applied ML engineering.
• MLOps tooling such as MLflow and modern experiment tracking platforms.
• Deploying models into production, including monitoring, testing and automation.
• AWS, with practical experience using SageMaker.
• Cloud and DevOps foundations including Docker and AWS
• Building scalable data and ML pipelines with solid engineering practices.
• You work well in fast paced environments, communicate clearly, and enjoy collaborating with cross functional teams.

What They Offer

• Competitive salary plus discretionary bonus.
• Hybrid working with three days each week in their London office.
• A high impact role within a growing data and AI team.
• Strong ownership, rapid development opportunities and exposure to modern ML tooling.
• A mission led environment focused on accelerating the transition to clean energy.

How To Apply

Please register your interest by sending your CV to Madison Barlow via the Apply link on this page.