Full job descriptionSenior 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.