MLOps Engineer

Job Description

DTG Global is partnering with a scaling fintech using advanced machine learning models to optimise risk and pricing in real time. They are looking to hire an MLOps Engineer to improve and maintain their ML infrastructure, ensuring models move seamlessly from research to production.

You’ll be joining a team that values clean engineering, practical solutions, and low operational overhead, working on ML systems that directly impact product and revenue.

What you’ll be doing

• Building and maintaining ML pipelines to automate the training, testing and deployment of models
• Developing monitoring and alerting systems for model drift, performance and reliability
• Working closely with Data Scientists and Engineers to streamline workflows from experimentation to deployment
• Managing and improving cloud infrastructure for scalable model serving and data processing (AWS/GCP)
• Championing best practices in CI/CD for ML models and infrastructure-as-code

What we’re looking for

• Experience in MLOps or strong DevOps/Platform Engineers moving into ML infrastructure
• Proficiency with Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
• Experience with containerisation (Docker, Kubernetes) in production environments
• Strong understanding of CI/CD workflows and automation tools
• Familiarity with cloud environments (AWS, GCP, or Azure) and infrastructure-as-code (Terraform, CloudFormation)

Nice to have

• Exposure to MLflow, SageMaker, or Vertex AI
• Experience with feature stores and managing model registries
• Knowledge of observability tools (Prometheus, Grafana) for monitoring ML systems
• Background in a regulated environment (fintech, healthtech) is a plus

Why this role

• Work with a tech-forward team that values quality engineering and clear processes
• Direct line of sight to product impact, not back-office tooling
• Flexible working with a London HQ if you prefer hybrid
• Competitive salary, strong benefits and an annual bonus

If you’re looking to advance your career in MLOps within a company that truly values its engineers and ML infrastructure, we’d love to connect.

Apply now or contact us for a confidential discussion.