CLOUD MACHINE LEARNING ENGINEER (AWS)
Vodafone Group (company site, opens in a new tab)5+ yrsPuneHybridDirect career pageEst. 22–40 LPA
Posted on 4 Sept
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and productionise machine learning systems and applications using AWS services tailored for local markets and group functions.
- Automate and maintain predictive model software, including managing data flow, data quality, and creating end-to-end ML pipelines with MLOps practices.
- Collaborate with architecture teams to evolve Big Data platform capabilities through reusable components, and research new technologies to improve ML application sustainability and delivery.
Minimum Requirements
- 5+ years of experience as AI/ML Engineer and 5+ years in BI or related software development.
- Mandatory hands-on experience with AWS services: SageMaker Pipelines, SageMaker Studio, CloudFormation, CloudTrail, SNS, EventBridge, CodePipeline, CodeBuild, CodeCommit.
- 3-year IT or IS degree or diploma (or related field) is essential; advanced degree and relevant cloud certification at professional or associate level preferred.
- Proficient programming skills in Java and Python with experience in distributed ML frameworks (e.g., TensorFlow, H2O) and Big Data frameworks (Hadoop, Spark, Hive).
Ideal Candidate Profile
- Experienced in managing agile software development lifecycles (Kanban or Scrum) in data science or ML engineering contexts.
- Strong background in building and scaling production-grade ML systems with robust data modelling, MLOps, and AWS-native pipeline automation.
- Comfortable collaborating with architecture teams to design reusable Big Data assets and optimizing data pipelines for efficiency and accuracy.