Additional responsibilities

• Maintain personal/professional development to meet the changing demands of the role, including all relevant regulatory and legislative training.
• When dealing with all customers, clients or colleagues ensure that we provide a clear, fair and consistent high quality service that presents a professional and positive image of CMC Markets.
• Take all reasonable steps to ensure appropriate confidentiality.
• Undertake such other duties, training and/or hours of work as may be reasonably required and which are consistent with the general level of responsibility of this role.

KEY SKILLS AND EXPERIENCE

• 3–7 years’ professional experience in MLOps, ML platform engineering, ML infrastructure, backend engineering, DevOps or SRE.
• Strong production Python skills, including clean APIs, testing, performance awareness and maintainable services.
• Experience deploying, serving and operating machine-learning models in production environments.
• Practical understanding of the ML lifecycle, including training, validation, inference, model release, monitoring and retraining.
• Experience designing CI/CD workflows and release processes for ML or other production software systems.
• Hands-on experience with at least one workflow or orchestration system used for ML training, validation or deployment.
• Comfort working with cloud infrastructure, containers, infrastructure as code and service networking.
• Strong understanding of observability, monitoring, alerting, incident response and common failure modes in ML systems.
• Ability to reason about system design, reliability and operational trade-offs—not just individual tools.
• Clear communication skills and the ability to work effectively with research, engineering, platform, security and product teams.

Nice to have

• Prior ownership of model monitoring, drift detection or automated retraining.
• Familiarity with model registries, feature stores and offline/online feature-consistency challenges.
• Experience supporting multiple models, services or teams on a shared ML platform.
• Exposure to regulated or high-reliability production environments.
• Experience with PyTorch or similar ML frameworks and model-serving technologies.

Technology environment

• Language: Python
• ML tooling: PyTorch or similar frameworks, experiment tracking and model registries
• Workflow orchestration: ML workflows for training, validation, deployment and retraining
• Deployment: Containers, model-serving frameworks and infrastructure as code
• Observability: Metrics, logging, tracing, alerting and monitoring across model, service and platform layers
• Cloud: Managed compute, storage and networking, with a provider-agnostic mindset

The technology stack will evolve. We value engineers who understand why systems are designed in particular ways and can adapt as requirements and tools change.

Why this role matters

Machine-learning models only create value when they are correct, observable and dependable in production. This role is responsible for making that happen.

You’ll reduce the gap between promising experiments and production systems that can be trusted by downstream products and customers. Your work will improve the reliability, speed and scalability of the ML platform across the organisation.

If you care about operational clarity, robust engineering and building ML systems that do not silently fail, this role gives you direct leverage over the success of our machine-learning capabilities.

CMC Markets is an equal opportunities employer and positively encourages applications from suitably qualified and eligible candidates regardless of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age.