Join Us

At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.

What you’ll do

Role purpose:

The Machine Learning Engineer is responsible for designing, building, deploying, and maintaining scalable machine learning models and data-driven solutions that solve real-world business problems. This role bridges data science and software engineering, ensuring that machine learning models are production-ready, reliable, and performant.
The MLE works closely with data scientists, data engineers, product managers, and business stakeholders to translate analytical insights into robust, deployable systems.

Key Accountabilities:

• Identify opportunities for automation and process optimization across various departments and functions;
• Design, develop, and implement automated solutions using appropriate tools and technologies;
• Collaborate with cross-functional teams to gather requirements and define automation objective;
• Conduct feasibility studies and analyze the cost-benefit of automation initiatives;
• Perform testing and debugging of automated processes to ensure accuracy and reliability;
• Monitor and maintain automated solutions, including troubleshooting and resolving issues;
• Make decisions on the most effective automation approaches for different processes;
• Recommend process improvements and optimizations based on automation outcomes.;
• Design, develop, train, and evaluate machine learning models for predictive, classification,recommendation, or optimization use cases;
• Translate data science prototypes into production-grade machine learning pipelines;
• Deploy models using APIs, batch jobs, or streaming architectures;
• Monitor model performance, data drift, and retraining requirements in production;
• Collaborate with data engineers to build and optimize data pipelines for model training inference and other data Related;
• Perform feature engineering and feature selection to improve model accuracy and performance;
• Ensure models comply with data privacy, security, and regulatory requirements;
• Apply responsible AI principles, including fairness, explainability, and transparency;
• Write clean, maintainable, and well-tested code using best software engineering practices;
• Implement CI/CD pipelines for machine learning workflows ;
• Use containerization and orchestration tools (e.g., Docker, Kubernetes) for scalable deployments;
• Apply MLOps practices including versioning, experiment tracking, and model lifecycle management;
• Work closely with data scientists to operationalize models;
• Partner with product and business teams to understand requirements and success metrics;
• Communicate model behaviour, limitations, and outcomes to non-technical stakeholder. 

What we are looking in you:

• Bachelor’s or master’s degree in computer science, Engineering, Data Science, Mathematics, or a related field;
• 3+ years of experience in machine learning, software engineering, or applied data science (level dependent);
• Experience deploying ML models in production environments;
• Familiarity with cloud platforms (AWS, Azure, or GCP) and managed ML services;
• Experience with CI/CD tools and version control systems (Git);
• Strong programming skills in Python (required); familiarity with Java, Scala, or C++ is an advantage;
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost;
• Solid understanding of supervised and unsupervised learning, model evaluation, and optimization techniques;
• Experience with data processing tools and frameworks (e.g., Pandas, NumPy, Spark);
• Knowledge of REST APIs and microservices architecture; 

Who we are

We are a leading international Telco, serving millions of customers. At Vodafone, we believe that connectivity is a force for good. If we use it for the things that really matter, it can improve people’s lives and the world around us. Through our technology we empower people, connecting everyone regardless of who they are or where they live and we protect the planet, whilst helping our customers do the same.

Belonging at Vodafone isn’t a concept; it’s lived, breathed, and cultivated through everything we do. You’ll be part of a global and diverse community, with many different minds, abilities, backgrounds and cultures. ;We’re committed to increase diversity, ensure equal representation, and make Vodafone a place everyone feels safe, valued and included.

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, please refer to https://careers.vodafone.com/application-adjustments/ for guidance.

Together we can.