Location
London (Hybrid working model with part-time remote work available)

Hours
Full Time

Salary
Competitive salary with excellent benefits

About the Role
At The Football Association, we are harnessing the power of data, machine learning and advanced analytics to help shape the future of football. As we move from experimentation to real-world impact, we are seeking an ML Engineer to build platforms, tools and operational foundations that enable innovation at scale. You will work alongside talented colleagues across data science, analytics and technology to ensure machine learning models and analytical products are deployed, monitored and trusted in live environments. Your role will involve creating robust, scalable solutions that deliver value across the organisation.

Key responsibilities include:
- Building, operating and improving production-grade ML and analytics pipelines that are reliable, reproducible and well-governed.
- Supporting packaging, deployment and lifecycle management of machine learning models.
- Implementing and maintaining MLOps practices such as versioning, automated testing, monitoring, logging and controlled release processes.
- Establishing model observability including performance tracking, drift monitoring and alerting.
- Acting as a technical enabler for data scientists and analysts by providing tooling, patterns and guardrails.
- Translating analytical and business requirements into scalable, supportable platform components aligned with FA architecture and governance.
- Supporting the transition from prototype to production without redefining analytical ownership or methodology.
- Contributing to shared engineering standards, templates and automation to reduce friction for analytics and data science teams.
- Ensuring ML services are secure, compliant, cost-aware and auditable in line with FA policies.
- Maintaining clear technical documentation to support handover, continuity and internal assurance.
- Complying with all company policies to maintain high standards of health, safety and well-being.

We are committed to creating an inclusive and supportive working environment with flexible working options and encourage applications from diverse backgrounds and experiences.

Experience
- Strong Python engineering skills including testing, packaging and environment management.
- Hands-on experience operationalising ML or advanced analytics in cloud environments such as Microsoft Fabric, Azure ML or Azure Synapse.
- Practical experience with CI/CD pipelines (Azure DevOps or GitHub Actions).
- Solid understanding of security, governance, data quality and operational reliability in production systems.
- Familiarity with common ML frameworks (scikit-learn, PyTorch, TensorFlow) sufficient to productionise models authored by others.

Beneficial Experience
- Experience with model registries, feature management or responsible AI tooling.
- Exposure to monitoring and observability platforms for data/ML systems.
- Knowledge of containerisation (Docker) or cloud orchestration patterns.

About you
- Collaborative and pragmatic, sharing knowledge and ensuring best practices within a team.
- Comfortable working in a matrix organisation with multiple partner teams.
- Able to explain complex technical concepts clearly to non-engineering stakeholders.

Qualifications
No specific qualifications required; emphasis is on relevant experience, skills and a collaborative mindset.