We are seeking a highly skilled Machine Learning Engineering Lead to drive the quality, scalability, and standardisation of machine learning solutions across the organisation. This role focuses on designing, developing, deploying, and maintaining end-to-end ML solutions while establishing technical standards, coding practices, and operational excellence. The successful candidate will combine strong software engineering expertise with advanced machine learning knowledge, work closely with stakeholders across distributed teams, and provide technical leadership, mentoring, and guidance to engineering colleagues.

Provide technical leadership, mentoring, and guidance to junior and senior machine learning engineers, acting as a key technical reference within the team.

Design, develop, and deliver solutions for large-scale, real-world machine learning challenges.

Create, maintain, and optimise data pipeline platforms, ML pipelines, workflows, and automation solutions.

Oversee project priorities, deliverables, timelines, and technical quality standards.

Refactor and optimise machine learning algorithms to ensure production readiness and operational efficiency.

Design and develop cloud-based integrations and APIs.

Deliver containerised microservices following test-driven development practices.

Enable and integrate cloud capabilities into developed tools and platforms.

Build web applications and tools that support data scientists and facilitate customer consumption of machine learning services.

Follow accessibility standards, cross-browser compatibility requirements, and established engineering best practices.

Promote high-quality software engineering practices through code reviews and collaborative development.

Collaborate with planners, product teams, and stakeholders to design, develop, and operate tools that meet business requirements.

Support troubleshooting, root cause analysis, and issue resolution activities in collaboration with other teams.

Lead technical training sessions, contribute to standard operating procedures, and support engineering recruitment activities.

Conduct peer programming, knowledge sharing, and continuous improvement initiatives across the engineering community.

Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline, or equivalent practical experience.

Demonstrated experience in machine learning engineering, software engineering, and production-scale solution delivery.

Strong expertise in machine learning algorithms, statistical modelling, and data analysis techniques.

Proficiency in Python, R, Java, or similar programming languages.

Experience with machine learning frameworks such as TensorFlow, scikit-learn, or equivalent technologies.

Strong knowledge of data pre-processing, feature engineering, and large-scale data manipulation.

Solid foundation in mathematics, statistics, and probability theory.Experience deploying, monitoring, and maintaining machine learning models throughout the full ML lifecycle.

Familiarity with cloud platforms including AWS, Microsoft Azure, or Google Cloud.

Experience working with big data and distributed technologies such as Hadoop, Spark, and Kubernetes.

Strong understanding of Generative AI concepts and prompt engineering practices.

Experience working within international and geographically distributed teams.

Ability to facilitate workshops, validation sessions, and stakeholder discussions.

Excellent analytical, problem-solving, communication, and collaboration skills.

Experience mentoring colleagues and delivering technical training.

Ability to create and maintain standard operating procedures and engineering standards.

Commitment to continuous learning and adapting to emerging technologies and industry trends.

Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.

Opportunity to work on large-scale machine learning and AI initiatives with global impact.

Exposure to modern cloud, data engineering, and MLOps technologies.

Chance to influence engineering standards, coding quality, and technical strategy.

Collaborative international working environment with cross-functional stakeholders.

Opportunities to mentor colleagues and contribute to the growth of the wider engineering community.

Continuous learning through exposure to emerging technologies, Generative AI, and advanced machine learning practices.

Advanced machine learning lifecycle management and production deployment practices.

Scalable data engineering and cloud-native architecture design.MLOps, automation, orchestration, and platform engineering capabilities.Leadership, mentoring, stakeholder management, and technical coaching skills.

Enterprise-scale API development and microservices architecture.

Generative AI implementation and prompt engineering best practices.

Technical governance, software quality assurance, and engineering standardisation.

Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.

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