Senior MLOps Engineer (Recommendation Systems)

London

Inside IR35

£600 - £650

Immediate Start

2 Days a week In Office

6 Month Duration

The Company

They are a well-established online business investing heavily in machine learning and AI to enhance customer engagement and product discovery. Their data science and engineering teams build and deploy large-scale recommendation and ranking solutions that operate in real time. Alongside traditional machine learning, they are also exploring the use of large language models across product and content-focused use cases.

The Role and Deliverables

• Build, deploy, and maintain machine learning models within real-time recommendation and ranking systems.
• Develop robust MLOps solutions to support online inference and low-latency production environments.
• Work across a variety of machine learning frameworks, including TensorFlow and PyTorch.
• Support the deployment, monitoring, and optimisation of production machine learning services.
• Collaborate with data scientists and machine learning practitioners to operationalise models at scale.
• Contribute to the deployment of LLM-based solutions, including product retrieval and AI-driven content processing applications.

Your Skills & Experience

• Strong experience in MLOps, machine learning engineering, or production ML deployment.
• Proven capability deploying machine learning models into real-time, customer-facing environments.
• Experience working with recommendation systems, ranking models, or other low-latency online ML applications.
• Strong software engineering and production engineering mindset.
• Experience with TensorFlow, PyTorch, or similar machine learning frameworks.
• Understanding of model serving, monitoring, scalability, and production infrastructure.
• Exposure to LLMOps or deploying large language models in production environments is beneficial.
• Experience within sectors such as e-commerce, online platforms, gaming, fraud detection, live media, or conversational AI would be advantageous.

How to Apply

If you are an experienced MLOps Engineer with a track record of deploying machine learning systems in real-time production environments, apply now to learn more about this contract opportunity.