Machine Learning Engineer

As ML Engineer you will be responsible for bridging the gap between data science experimentation and production-grade scalable ML systems.

You will own the engineering excellence required to take validated models from data scientists and deploy them reliably across the organisations fragmented platform estate. You will work across the full ML Operations lifecycledesigning deployment pipelines implementing model serving infrastructure establishing monitoring and governance frameworks and automating retraining workflows. Your role is critical to standardising practices across platforms and ensuring models can be built deployed and maintained consistently regardless of underlying infrastructure differences.

You will collaborate closely with Data Scientists on model productionisation AI Engineers on platform infrastructure requirements and Analytics Engineering on data pipeline dependencies and reliability.

Key Roles & Responsibilities

• Design build and maintain ML deployment pipelines and model serving infrastructure for both real-time and batch inference workloads across multiple platforms
• Establish comprehensive model monitoring alerting and performance tracking systems in production environments to ensure reliability and early problem detection
• Implement model versioning reproducibility and automated retraining workflows that enable fast iteration whilst maintaining stability
• Partner with Data Scientists to productionise validated experimental models translating research outputs into robust maintainable systems
• Contribute to platform standardisation efforts across the fragmented estate identifying common patterns and opportunities for reuse
• Design and implement CI/CD pipelines tailored for ML workloads ensuring quality traceability and repeatability
• Support governance and compliance requirements through technical documentation audit trails and reproducible deployment processes
• Monitor and optimise compute resource allocation and infrastructure costs across platforms applying FinOps principles
• Collaborate with Analytics Engineering to ensure data pipeline reliability quality and performance for ML workloads
• Contribute to team knowledge sharing and best practice documentation across the ML Engineering function

Qualifications :

Job Requirements Knowledge & Experience

We are looking for someone passionate and dedicated about ensuring our ML solutions are scalable secure and responsibility deployed.

• Proven experience in ML engineering or ML Operations roles with multiple production model deployments at scale
• Strong Python programming skills with software engineering fundamentals: testing version control code quality and design patterns
• Hands-on experience with ML platforms such as Azure AI Foundry Azure ML Databricks GCP or equivalent
• Solid understanding of containerisation and orchestration technologies
• Demonstrable experience designing and implementing CI/CD pipelines for machine learning workloads

Additional Information :

Need to know

We are regulated by the Financial Conduct Authority and all offers of employment for this role are subject to background checks including criminal (DBS) and financial checks to meet the regulators standards.

We believe everyone should have the opportunity to interview for a role that matches their collaboration with our Talent Diversity & Inclusion teams and our employee-led DEI Networks we identified a range of reasonable adjustments to help you feel comfortable and perform at your best self during the interview process. If you require any reasonable adjustments or have an accessibility request as part of your recruitment journey for example extended time or breaks in between online assessments a sign language interpreter or assistive technology please contact your recruiter directly or email for guidance.

We use AI in different parts of our business to boost innovation improve efficiency and create new opportunities. We know many candidates use AI to fine-tune their CVs or prepare for interviews but what we really care about is your unique experiences and achievements.

During the interview we want you to rely on your own knowledge and skills to show us who you really areyour personality creativity and abilities. Above all were looking for authenticity and cant wait to get to know the real you.

 #VodafoneThree

Remote Work :

No

Employment Type :

Full-time