3 months ago
London, United KingdomSenior
Responsibilities
- Own and evolve the platform infrastructure powering Xantura’s AI services across multiple clients.
- Deploy and manage machine learning models using Azure ML endpoints, batch endpoints, and AKS.
- Build and maintain production orchestration pipelines with Dagster for training, inference, and retraining.
- Implement reliable, scalable, secure model hosting, monitoring, observability, and lifecycle management.
- Ensure AI systems are transparent, explainable, auditable, and aligned with Responsible AI principles and UK GDPR.
- Contribute to AI capability building, technical feasibility guidance, and governance standards across delivery and consulting teams.
Requirements
- 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 MLOps, Platform Engineering, or Infrastructure Engineering 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.
- Practical experience deploying, scaling, and troubleshooting containerised workloads on Kubernetes in production.
- Experience building and maintaining CI/CD pipelines for automated testing, building, and deployment of ML services.
- Experience implementing infrastructure-as-code using Terraform, Bicep, Pulumi, or equivalent tools.
- Experience implementing production monitoring and observability, including metrics, alerting, logging, and dashboards.
- Experience with pipeline orchestration using Dagster, Airflow, Prefect, or similar.
- Bonus experience with model serving, multi-tenant systems, asynchronous APIs, vector databases such as Qdrant, and production data and model pipelines.
- Familiarity with Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, and Azure Key Vault.
Benefits
- Hybrid London role with office attendance expected 1–2 days per week, remote work available except for face-to-face team and client meetings.
- Occasional travel for on-site client engagements.
- Flexible hours around life commitments.
- Training and development opportunities.
- 25 days annual leave plus bank holidays.
- Company pension and private medical insurance.
- Enhanced parental leave policies.
- Cycle to work scheme, flu vaccinations, eye tests, and contribution toward glasses for VDU use.
- Employee Assistance Programme, mental health and wellbeing support, remote GP access, counselling and therapy, physiotherapy, and medical second opinions.
Tech Stack
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