Machine Learning Engineer

We’re hiring an Machine Learning Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: you’ll design and operate data pipelines that feed models, and you’ll build the tooling that trains, deploys, monitors, and retrains them.

You’ll work closely with research engineers and product teams, taking models from experimentation to production-grade systems with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale.

What You’ll Work On

• Build and operate ML lifecycle infrastructure, including model packaging, deployment, versioning, rollback, and CI/CD.
• Implement model monitoring, experiment tracking, and reproducibility.
• Build and maintain reliable batch and near-real-time data and feature pipelines, ensuring data quality, lineage, and schema evolution.
• Own the reliability, availability, latency, and freshness of ML systems, including production debugging and observability.
• Collaborate with platform and security teams on infrastructure, access, secrets, and compliance.
• Write production-grade Python and establish testing, validation, and release practices for ML systems.
• Balance research flexibility with production stability through sound engineering trade-offs.

Required Qualifications

• 3 - 7 years of professional experience in ML Ops, Data Engineering, or adjacent backend roles
• Strong production Python skills (clean APIs, testing, performance awareness)
• Experience deploying and operating ML models in production environments

Solid understanding of:

• Model training vs. inference requirements
• Batch vs. streaming data pipelines
• Failure modes in data-driven systems
• Hands-on experience with at least one modern orchestration or workflow system
• Comfort working with cloud infrastructure and containerized workloads
• Ability to reason about system design, not just tool usage

Why This Role Matters

Our models only create value when they are correct, observable, and dependable in production. This role is responsible for that reality. You’ll reduce the gap between promising experiments and systems that can be trusted by downstream products and customers.

If you care about data correctness, operational clarity, and building ML systems that don’t silently fail, this role gives you direct leverage over the success of our entire ML platform.

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.