Jobs / Royal Mail
ML Ops Engineer
Royal Mail · London, ENG, United Kingdom
London, ENG, United KingdomFull timeExp: 3+ yrsOnsite
Remuneration
Car allowance, healthcare, up to 18% annual bonus potential, pension, annual leave, and other stated benefits
Location
London, ENG, United Kingdom
Visa sponsorship
Not specified
Job summary
The Machine Learning Engineer builds and operates production-grade machine learning systems to improve business outcomes, customer experience, and operational efficiency. The role covers scalable training, testing, deployment, and monitoring pipelines; model optimisation; CI/CD automation; and resilient production APIs, working with Data Scientists and platform teams. The work uses Python, frameworks such as TensorFlow, PyTorch, or Kubeflow, cloud platforms including Azure, AWS, or GCP, and Kubernetes.
Benefits
Car allowanceHealthcareUp to 18% annual bonus potential25 days of annual leave plus bank holidays, increasing with servicePensionEnhanced family leaveCompany sick payFunded dental insuranceEmployer-funded health assessment every two yearsBenefits accountWellbeing, financial, and social support services
Qualifications
- Experience delivering machine learning solutions into production as a Machine Learning Engineer or in a similar role
- Strong Python development skills and experience with TensorFlow, PyTorch, or Kubeflow
- Experience designing, deploying, and maintaining scalable machine learning platforms and pipelines
- Knowledge of Azure, AWS, or GCP cloud environments
- Experience with containerisation and orchestration technologies such as Kubernetes
- Strong understanding of software engineering, DevOps, and MLOps principles
- Experience building and supporting production APIs and machine learning services
- Collaborative approach with strong communication and stakeholder engagement skills
- At least three years of experience in Machine Learning, AI Engineering, or a related field
Responsibilities
- Design and implement scalable machine learning pipelines for training, testing, deployment, and monitoring
- Optimise production model performance, reliability, and scalability
- Build CI/CD processes and automated machine learning delivery workflows
- Operationalise machine learning models and AI solutions with Data Scientists
- Promote MLOps best practices across the data community
- Deploy and manage machine learning workloads using cloud technologies and approved tools
- Maintain resilient, secure, and scalable production APIs and machine learning services
- Contribute to engineering standards, continuous improvement, and technical innovation
Skills
AWSAzureGCPKubernetesPython
Work schedule
Full timeThree days per week in the London Farringdon office
Industry
Postal servicesData and AI
Relocation
No