Senior ML Ops Engineer
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Key skills for this role
Key Skills for This Role
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Key Responsibilities
- Continuously evolve the platform infrastructure powering all AI services (predictive modelling, NLP, knowledge representation, and agentic AI), ensuring reliable, scalable operation across a growing base of local authority clients.
- Deploy and manage ML models via Azure ML endpoints, batch endpoints , and AKS, enabling resilient, secure model hosting that accelerates client onboarding and ensures models remain performant and monitorable throughout their lifecycle.
- Ensure all ML systems are transparent, explainable, and auditable, aligned with Responsible AI principles and UK GDPR; essential where AI outputs inform decisions about vulnerable people in health and social care.
- Design, build, and maintain production-grade orchestration pipelines (Dagster) supporting model training, inference, and retraining, ensuring data from local authority systems is timely, accurate, and fit for purpose before it reaches ML services.
- Contribute to organisation-wide AI capability building, sharing best practice with delivery and consulting teams, advising on technical feasibility, and shaping governance standards as the AI function scales.
What are we looking for?
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
4+ years of professional experience in an MLOps, Platform Engineering, or Infrastructure Engineering role supporting ML or data-intensive systems.
Strong programming skills and production experience in Python.
Expertise in Azure-native MLOps, including model endpoints, pipelines, registries, environments, and compute management.
Deploying, scaling, and troubleshooting containerised workload on Kubernetes in production
Building and maintaining CI/CD pipelines (Azure DevOps or equivalent) for automated testing, building, and deployment of ML services
Implementing infrastructure-as-code (Terraform, Bicep or Pulumi)
Implementing monitoring and observability for production systems, including metrics, altering, logging, and dashboarding (e.g. Prometheus, Grafana)
Pipeline orchestration using Dagster, Airflow, Prefect, or similar
Practical experience with model serving infrastructure – batch and/or real-time inference at scale.
Experience operating multi-tenant systems, particularly scaling infrastructure across multiple clients or business units.
Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services.
Experience setting up, and optimising vector databases, e.g. Qdrant, and integrating with other services
Proficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD).
Deep familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault).
What can we offer you?
Competitive salary reviewed annually
Work for a passionate, mission-driven company solving society’s big problems
Work flexible hours around life commitments with a focus on delivering company value rather than hours worked
Ability to work remotely (excluding face-to-face Team Meetings and client meetings)
Training and development opportunities
25 days annual leave (plus bank holidays)
Company pension
Private medical insurance
Generous enhanced parental leave policies
Cycle to work scheme
Flu Vaccinations,
Eye Test and contribution towards Glasses for VDU use
Employee Assistance Programme Mental health and wellbeing support Remote GP access Counselling/therapy Physiotherapy Medical second opinions
Mental health and wellbeing support
Remote GP access
Counselling/therapy
Physiotherapy
Medical second opinions
About Xantura
UK private software company providing AI and data analytics to public-sector organizations for earlier intervention and outcomes.
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