More details about the Machine Learning Engineer

Location: London – hybrid, 2 days a week in office. Reporting to Head of AI.

We are looking for a talented Machine Learning Engineer who thrives in environments where reliability, scale, and impact truly matter.

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, partners and all stakeholders across the UK property market.

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.

As a Machine Learning Engineer 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.

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• 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 (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 (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.
  

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• 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).
  
• Expertise in MLOps: CI/CD pipelines, Docker, Kubernetes, workflow orchestration (Airflow, Prefect), and automation.
  
• Experience across the full ML lifecycle. Can design for long‑term scalability, reliability, and resilience.
  
• Strong programming skills with Python – essential. Hands‑on experience with ML frameworks (PyTorch, TensorFlow, Scikit‑learn).
  
• Experience with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow); AWS SageMaker or similar is also valued.
  
• Operated in distributed computing environments, working with large datasets and parallelised processing.
  
• Effective communicator of technical concepts and trade‑offs to both technical and non‑technical audiences.
  
• Proactive, detail‑oriented, and motivated to learn emerging ML engineering tools.
  
• Experience working within cross‑functional teams and collaborating across teams.
  
• Keeps abreast of the latest advancements in machine learning engineering, MLOps, and generative AI.
  

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• 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.
  

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 the tools, expertise, trust and belief to make it happen. We’re home to the UK’s largest choice of properties, and are the go‑to destination for millions of people planning their next move.

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• Cash plan for dental, optical and physio treatments
  
• Private Medical Insurance, Pension and Life Insurance, Employee Assistance Plan
  
• 27 days holiday plus two paid volunteering days a year to give back, and holiday buy schemes
  
• Hybrid working pattern with 2 days in office
  
• Contributory stakeholder pension
  
• Life assurance at 4× your basic salary to a spouse, family member or other nominated person in your life
  
• Competitive compensation package
  
• Paid leave for maternity, paternity, adoption & fertility
  
• Travel Loans, Bike to Work scheme, Rental Deposit Loan
  
• Charitable contributions through Payroll Giving and donation matching
  
• Access deals and discounts on travel, electronics, fashion, gym memberships, cinema discounts and more
  

As an Equal Opportunity Employer, Rightmove will never discriminate on the basis of age, disability, sex, race, religion or belief, gender reassignment, marriage, civil partnership, pregnancy or maternity, or sexual orientation. At Rightmove, we believe that a diverse and inclusive workforce leads to better innovation, productivity, and overall success. We are committed to creating a welcoming and inclusive environment for all employees, regardless of their background or identity, to develop and promote a diverse culture that reflects the communities we serve.