CLOUD MACHINE LEARNING ENGINEER

What you’ll do

• Design and develop machine learning systems and implementation patterns.
• Automate predictive model software, including model training.
• Productionise data science prototypes and develop machine learning applications aligned to data science requirements.
• Facilitate the flow of data between ML/AI models and the organisation’s data systems.
• Enhance data pipelines to ensure data is clean, accurate, and optimised for machine learning models.
• Partner with the architecture team to evolve Big Data platform capabilities (reusable assets/patterns) and components to meet business requirements and objectives.
• Research, investigate, and evaluate new technologies and methods to improve delivery and sustainability of machine learning applications and services.
• Contribute to defining best practice for agile development of applications running on the Big Data platform.

Who you are

• Experience managing the development lifecycle for agile software development projects (Kanban or Scrum exposure).
• Robust data modelling and data architecture skills.
• Knowledge of Big Data frameworks such as Hadoop, Spark, Hive, Yarn, and Airflow.
• Experience with distributed ML frameworks (for example H2O and/or TensorFlow) and various ML libraries.
• Proven experience creating and deploying end-to-end ML pipelines in production, including MLOps.
• Programming experience in Java and Python.
• Experience with containerisation (Docker/Kubernetes) or cloud alternatives is advantageous.
• Mandatory working experience with AWS services including: SageMaker Pipelines, SageMaker Studio, CloudFormation, CloudTrail, SNS, EventBridge, CodePipeline, CodeBuild, CodeCommit.
• Experience with other distributed technologies, NoSQL databases, and streaming technologies is desirable.
• Strong written and verbal communication, with excellent interpersonal and collaboration skills.
• Must have technical / professional qualifications:
  • 3-year IT or IS degree or diploma (or related field) is essential; an advanced degree in Computer Science/Math/Statistics (or related discipline) is an advantage.
  • Relevant cloud certification at professional or associate level.
  • 5+ years of relevant experience as an AI/ML Engineer.
  • 5+ years of BI or related software development experience.

Not a perfect fit?

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.

What's in it for you

• Opportunities to deliver business value by enabling scalable ML capabilities for local markets and group functions.
• The chance to work on production-grade ML systems, end-to-end pipelines, and MLOps practices on AWS.
• Collaboration with architecture teams to shape reusable Big Data platform assets and engineering patterns.
• Scope to explore and evaluate new technologies and methods to improve sustainability and delivery of ML applications and services.

What skills you will learn

• Strengthening best practices for productionising data science prototypes into reliable ML applications.
• Deepening hands-on expertise in AWS-native MLOps and pipeline automation (including SageMaker and AWS developer tools).
• Enhancing Big Data platform design skills through reusable patterns, components, and data pipeline optimisation.
  • Improving cost and resource efficiency approaches across compute, network usage, and platform objectives.