Senior ML Ops Engineer

Xantura; Greater London; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

25 days annual leave

Private medical insurance

Training and development opportunities

Company pension

Work flexibility

Job summary

Xantura Limited is looking for a Senior ML Ops Engineer to join the Platform Delivery team. You will evolve the backend platform supporting their AI services, ensuring reliable operations for local authority clients.

The ideal candidate has strong Python skills, experience in MLOps, and a solid background in Azure-native technologies. This hybrid role is based in London, requiring office attendance at least 1-2 days a week.

Qualifications

• 4+ years of experience in an MLOps, Platform Engineering, or Infrastructure role.
• Strong programming and production experience in Python.
• Experience creating CI/CD pipelines for ML services.

Responsibilities

• Evolve platform infrastructure for AI services.
• Deploy and manage ML models via Azure ML.
• Ensure ML systems are auditable and align with Responsible AI principles.

Skills

Python programming

MLOps expertise

Kubernetes

Azure DevOps

Terraform

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Azure

Dagster

Prometheus

Grafana

Job description

Senior ML Ops Engineer

Department: Platform Delivery

Employment Type: Permanent - Full Time

Location: London

Description

In this role you will work in the Platform team – a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.

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?

We’d love to hear from you if you have:

• 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.

Clear evidence of practical experience across the following:

• 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, alerting, logging, and dashboarding (e.g. Prometheus, Grafana)
• Pipeline orchestration using Dagster, Airflow, Prefect, or similar

Bonus points if you have:

• 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).

Location – This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1‑2 days per week. Some travel is also required for on‑site client engagements as needed.

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 insuranceGenerous 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