Job Specifications
We are looking for a
Machine Learning Engineer
Location: London - hybrid, 2 days a week in office
Reporting to: Head of AI
The role
At Rightmove, you’ll join a close-knit, collaborative AI team that’s developing, shipping and operating live ML/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market. We are looking for a talented Machine Learning Engineer who thrives in environments where reliability, scale, and impact truly matter.
You’ll be at the heart of a greenfield opportunity - building, deploying, and operating machine learning systems that leverage Rightmove’s data at large scale. You’ll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help us move from first launches to robust, sustainable production.
In this role, you will work in a cross-functional team to productionise machine learning and AI models, ensuring they are robust, scalable, and measurable. You’ll collaborate closely with data scientists, engineers, and product teams to automate workflows, monitor performance, and retrain models as needed.
You’ll bring a passion for building reliable ML infrastructure, a strong technical foundation in modern machine learning engineering, and a track record of working in environments where reliability and scale are paramount.
Our Data & Analytics team has grown significantly over the last 18 months, with strong ongoing investment in infrastructure, tooling, and talent. This is a unique opportunity to own high-impact projects, help define our AI roadmap, and influence the future of how the UK engages with property.
A typical week as a Machine Learning Engineer might involve;
Designing, building, and maintaining ML pipelines for training, deployment, monitoring, and retraining at scale.
Working with data scientists to take models from development to production-grade systems, ensuring scalability, reproducibility, and robustness.
Automating feature engineering and data pipeline processes, ensuring reproducibility and auditability.
Implementing monitoring and observability to detect drift, bias, and performance degradation, and setting up rollback/recovery processes.
Using MLOps tools (e.g., Vertex Pipelines, Kubeflow, Weights & Biases) for experiment tracking, model registry, and automated deployment.
Leveraging Docker/Kubernetes and workflow orchestration tools (Airflow, Prefect, Dagster).
Collaborating with product, design, and engineering teams to deliver ML features that directly impact customer experience.
Translating model performance into business metrics (e.g., accuracy vs cost/latency trade-offs).
Monitoring deployed solutions in production and automating retraining as needed.
Sharing knowledge across the data and AI community at Rightmove.
We’re looking for someone who;
Has impactful experience deploying and maintaining ML systems in production, ideally in larger, mature organizations or teams operating at significant scale (e.g., web-scale, distributed systems, cloud-native environments).
Brings expertise in MLOps: CI/CD pipelines, Docker, Kubernetes, workflow orchestration (Airflow, Prefect), and automation.
Has experience across and understands the full ML lifecycle. Can design for long-term scalability, reliability, and resilience.
Has strong programming skills with Python – essential. Has hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn).
Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued.
Has operated in distributed computing environments, working with large datasets and parallelized processing.
Can communicate technical concepts and trade-offs to both technical and non-technical audiences.
Is proactive, detail-oriented, and motivated to learn emerging ML engineering tools.
Has experience working within cross-functional teams and collaborating across teams.
Keeps abreast of the latest advancements in machine learning engineering, MLOps, and generative AI.
We would love someone to have any of the following
Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Data Science, or a related STEM subject (with a focus on software development or distributed systems).
3+ years of experience as an ML Engineer, MLOps Engineer, Data Engineer, or similar, in a larger-scale, production-focused environment.
Hands-on with model monitoring, observability, and retraining pipelines.
Exposure to feature stores, registries, and experimentation frameworks.
Familiarity with business-driven metrics and experience balancing ML performance with commercial goals.
Experience with generative AI and LLM frameworks for fine tuning, evaluation, deployment and serving desirable.
About Rightmove
Our vision is to give everyone the belief they can make their move. We aim to make moving simpler, by giving everyone the best place to turn to and return to for access to