ML Platform Engineer: Architect Reliable Production ML

CMC Markets; Greater London; On-site; GBP 65,000 - 100,000; Full time

Benefits offered by this job

Pension

Income Protection

Life Assurance

Health Insurance

Holiday 25 days

Breakfast provided

Discretionary Bonus

Job summary

CMC Markets is hiring an ML Ops Engineer to build and operate platform capabilities that move machine-learning models from experimentation into reliable production services.

You will own automation, deployment, observability and operational controls around the ML lifecycle, collaborating with research, software, platform and product teams to ensure reproducibility, scalability, security and dependability of ML systems.

Qualifications

• 3-7 years of professional experience in MLOps, ML platform engineering, or related fields.
• Experience designing CI/CD workflows for ML or production software.
• Hands-on experience with workflow/orchestration systems for ML training, validation or deployment.
• Strong production Python skills with clean APIs and maintainable services.
• Experience deploying and operating ML models in production environments.

Responsibilities

• Build repeatable workflows for model training, validation, promotion, deployment and retraining.
• Deploy and operate batch and online inference services in containerised cloud environments.
• Design and implement CI/CD pipelines for ML systems with automated testing and release controls.
• Manage experiment tracking, model metadata and reproducibility across research and production.
• Establish dashboards, alerts, and runbooks for incident detection and resolution.

Skills

Python programming

Observability

CI/CD

ML lifecycle

Container orchestration

Security & reliability

Experiment tracking

Model serving

Automation

Tools

PyTorch

Model registry

Containers

Infrastructure as code

CI/CD tooling

Job description

CMC Markets is hiring an ML Ops Engineer to build and operate platform capabilities that move machine-learning models from experimentation into reliable production services.

You will own automation, deployment, observability and operational controls around the ML lifecycle, collaborating with research, software, platform and product teams to ensure reproducibility, scalability, security and dependability of ML systems.