ML Ops Infrastructure Engineer (UK)

TWG Global AI; London; Hybrid; GBP 125,000 - 150,000; Full time

Job summary

A leading technology firm in London is looking for an ML Ops / Infrastructure Engineer to build and scale essential pipelines and tooling for AI applications. The ideal candidate will have 5+ years of experience in MLOps, deep expertise in cloud environments, and a strong background in CI/CD practices. This hybrid role offers competitive compensation and comprehensive benefits, contributing to significant innovations in AI and data-centric services.

Benefits

Competitive compensation

Leadership opportunities

Full range of medical benefits

Qualifications

• 5+ years in MLOps or related engineering roles.
• Deep experience with cloud environments and container orchestration.
• Proficiency with MLOps tooling and data infrastructure.

Responsibilities

• Architect and maintain ML infrastructure including data pipelines and feature stores.
• Build and manage automated CI/CD pipelines for ML.
• Implement observability frameworks for monitoring ML applications.

Skills

MLOps

AWS

Kubernetes

CI/CD

Python

Git

Tools

MLflow

Kubeflow

Terraform

Databricks

Job description

Overview

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees.

We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development.

You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation.

At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses.

The Role:

We are looking for an ML Ops / Infrastructure Engineer to build and scale the pipelines, platforms, and tooling that power TWG Global's AI-first future. As an MLOps/Infra Engineer, your focus will be on the systems and automation that make ML applications production-ready, reliable, and cost-efficient at scale. You'll design infrastructure that accelerates model development, ensures secure and compliant deployment, and enables continuous monitoring across a regulated enterprise environment.

Responsibilities:

• Architect and maintain ML infrastructure: data pipelines, feature stores, model registries, and distributed training systems.
• Build and manage automated CI/CD pipelines for ML, ensuring reproducibility, rollback, and seamless deployment.
• Implement observability frameworks: monitoring, logging, and alerting for data drift, model accuracy, latency, and infrastructure cost.
• Design and manage containerized, Kubernetes-based deployments for scalable inference and real-time AI applications.
• Integrate cloud services, APIs, and infrastructure with TWG's broader data and engineering ecosystem.
• Embed controls, audit trails, and governance into ML pipelines to meet compliance and regulatory requirements.
• Partner with Data Scientists to operationalize models, and with ML Engineers to ensure systems are robust, scalable, and efficient.
• Continuously automate workflows and optimize cost-to-serve, reducing the time from experimentation to production.

Requirements

• 5+ years in MLOps, infrastructure, or related engineering roles. Deep experience with cloud environments (AWS, Azure, or GCP) and container orchestration (Kubernetes, Docker).
• Strong knowledge of CI/CD pipelines, version control (Git), and infrastructure-as-code (Terraform, Helm, Pulumi, etc.).
• Proficiency with MLOps tooling: MLflow, Kubeflow, Vertex AI, SageMaker, or equivalent. Experience with data infrastructure (Spark, Kafka, Snowflake, Databricks, or Palantir Foundry).
• Solid programming skills in Python (preferred), plus one or more backend languages (Java, Scala, Go, C++).
• Familiarity with LLM/GenAI workflows and vector databases (Pinecone, FAISS, Milvus, Weaviate).
• Knowledge of observability stacks (Prometheus, Grafana, ELK, Datadog) for system monitoring.
• Comfort working in regulated industries (finance, insurance, healthcare) with strong compliance and governance needs.

Preferred, but not required:

• Hands-on with model governance, audit, and responsible AI frameworks.
• Experience with GPU clusters, distributed training, or HPC environments.
• Exposure to financial services systems (trading, risk management, or actuarial platforms).

Benefits

• Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services.
• Drive AI transformation for some of the most sophisticated financial entities.
• Competitive compensation, benefits, future equity options, and leadership opportunities.

This is a hybrid position based in the United Kingdom.

We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits.

TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.