Three UK
Telecommunications
MachineLearningEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Machine Learning Engineer at Three UK. Skills: ML engineering, ML Operations, production model deployments, Python, software engineering fundamentals, ML platforms, containerisation, orchestration technologies, CI/CD pipelines for ML workloads. bridging the gap between data science experimentation and production-grade, scalable ML systems. owning the engineering excellence required to take validated models from data scientists and deploy them reliably across the organisation's fragmented platfor”
What You'll Achieve.
building a network the UK can count on; connecting people, places and potential; closing the digital divide; empower communities; drive meaningful progress; building a workplace where different perspectives are welcomed, voices are heard, and everyone feels safe to show up as themselves; building responsibly; investing sustainably; creating opportunities that last; reimagining what a connected nation looks like; power businesses, services, and communities across the country; work on real challenges, with real impact; building a future that works better for everyone; ensuring our ML solutions are scalable, secure and responsibility deployed; ensure reliability and early problem detection; enable fast iteration whilst maintaining stability; ensuring quality, traceability, and repeatability; ensure data pipeline reliability, quality, and performance for ML workloads
Industry & Context.
problem detection
background checks, including criminal (DBS) and financial checks to meet the regulators standards
What They're Looking For.
Must Have
Proven experience in ML engineering or ML Operations roles with multiple production model deployments at scale, 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
What You'll Do.
bridging the gap between data science experimentation and production-grade
owning the engineering excellence required to take validated models from data scientists and deploy them reliably across the organisation's fragmented platform estate
working across the full ML Operations lifecycle—designing deployment pipelines
implementing model serving infrastructure
establishing monitoring and governance frameworks
and automating retraining workflows
standardising practices across platforms and ensuring models can be built
and maintained consistently regardless of underlying infrastructure differences
and maintaining ML deployment pipelines and model serving infrastructure for both real-time and batch inference workloads across multiple platforms
establishing comprehensive model monitoring
and performance tracking systems in production environments to ensure reliability and early problem detection
implementing model versioning
and automated retraining workflows that enable fast iteration whilst maintaining stability
contributing to platform standardisation efforts across the fragmented estate
identifying common patterns and opportunities for reuse
designing and implementing CI/CD pipelines tailored for ML workloads
supporting governance and compliance requirements through technical documentation
and reproducible deployment processes
monitoring and optimising compute resource allocation and infrastructure costs across platforms
applying FinOps principles
collaborating with Analytics Engineering to ensure data pipeline reliability
and performance for ML workloads
contributing to team knowledge sharing and best practice documentation across the ML Engineering function
How You'll Work.
Team & Collaboration
collaboration and connection with our colleagues; collaborate closely with Data Scientists on model productionisation; collaborate with AI Engineers on platform infrastructure requirements; collaborate with Analytics Engineering on data pipeline dependencies and reliability; Partner with Data Scientists to productionise validated experimental models; Contribute to platform standardisation efforts; Contribute to team knowledge sharing and best practice documentation
Full Job Description
VodafoneThree: Machine Learning (ML) Engineer Location: Newbury *Hybrid working Working Hours: Full time 37.5 hours per week – Mon – Fri * Hybrid We believe that through collaboration and connection with our colleagues we can achieve great things. Our hybrid working approach allows our people to work both in the office and at home, providing the flexibility and resources you need to succeed in your role. We don't require you to be in on specific days; instead, we ask people to come into the office 2-3 days each week. You should work with your line manager to understand what their expectations are for you, your specific role and your team. Who We Are We’re here to build a network the UK can count on – one that connects people, places and potential. Because no matter where you live, what your background is, or how you get online – we think everyone deserves the same chance to stay connected, and with VodafoneThree, that future’s being built – today. We’re creating more than the UK’s best network. We’re helping close the digital divide, empower communities and drive meaningful progress. We believe that everyone should feel they belong. Whoever you are and whatever your story, there’s space for you here. We’re building a workplace where different perspectives are welcomed, voices are heard, and everyone feels safe to show up as themselves. You’ll join a team that genuinely cares – about each other, about our customers, and about the future we’re building. From day one, you’ll be welcomed, valued and encouraged to bring your whole self to work. Why VodafoneThree Join us and you’ll be at the heart of change. That means building responsibly, investing sustainably and creating opportunities that last. We’re not just expanding connectivity; we’re reimagining what a connected nation looks like. With £11bn invested in 5G and digital infrastructure, your work will directly power businesses, services, and communities across the country. You’ll work on real challenges, with real
Applying for this Machine Learning Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on SmartRecruiters
- SmartRecruiters often includes a video screening step — check camera and mic permissions.
- Link your GitHub or portfolio directly in the profile section for technical roles.
- Applications may be reviewed by AI scoring before reaching a recruiter — use keywords from the job description.
ANONYMOUS · UNFILTERED
What do employees actually say about Three UK?
Real rants from real employees. Read before you apply.