Own the infrastructure layer that all of Xantura's AI services depend on to operate and scale.
Be responsible for how ML models and NLP systems are deployed, monitored, and maintained.
Continuously evolve the platform infrastructure powering all AI services (predictive modelling, NLP, knowledge representation, and agentic AI).
Deploy and manage ML models via Azure ML endpoints, batch endpoints, and AKS.
Ensure all ML systems are transparent, explainable, and auditable, aligned with Responsible AI principles and UK GDPR.
Design, build, and maintain production-grade orchestration pipelines (Dagster).
Contribute to organisation-wide AI capability building, sharing best practice with delivery and consulting teams.

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

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

Senior ML Ops Engineer

Key skills