Pune, MH, IN
Live, first seen by us 61 days agoEmployment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
We are seeking a Cloud ML Engineer (AWS) within Data & Analytics GSL to use ML/AI expertise alongside strong programming and software engineering skills to make machine learning models and analyses easier to use and access.
Design and develop machine learning systems and implementation patterns
Productionise data science prototypes into ML applications
Automate predictive model software, including model training
Enhance data pipelines so data is clean and optimised for ML models
Facilitate data flow between ML/AI models and the organisation's data systems
We are seeking a Cloud ML Engineer (AWS) within Data & Analytics GSL to use ML/AI expertise alongside strong programming and software engineering skills to make machine learning models and analyses easier to use and access. The role supports local markets and group functions to obtain business value from machine learning, and focuses on designing ML systems, productionising prototypes, enabling robust data flows, and evolving Big Data capabilities through reusable assets and patterns.
Design and develop machine learning systems and implementation patterns.
Productionise data science prototypes and develop machine learning applications aligned to data science requirements.
Automate predictive model software, including model training.
Enhance data pipelines to ensure data is clean, accurate, and optimised for machine learning models.
Facilitate the flow of data between ML/AI models and the organisation’s data systems.
Experience managing the development lifecycle for agile software development projects (Kanban or Scrum exposure).
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.
Knowledge of Big Data frameworks such as Hadoop, Spark, Hive, Yarn, and Airflow.
5+ years of relevant experience as an AI/ML Engineer.
Experience with distributed ML frameworks (for example H2O and/or TensorFlow) and various ML libraries.
5+ years of BI or related software development experience.
Experience with other distributed technologies, NoSQL databases, and streaming technologies is desirable.
VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.
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- 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.
About this Role We are seeking a Cloud ML Engineer (AWS) within Data & Analytics GSL to use ML/AI expertise alongside strong programming and software engineering skills to make machine learning models and analyses easier to use and access. The role supports local markets and group functions to obtain business value from machine learning, and focuses on designing ML systems, productionising prototypes, enabling robust data flows, and evolving Big Data capabilities through reusable assets and patterns. What you’ll do
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation.
As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.
We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.
#VOIS #BeUnrivalled #CreateTheFuture
We are seeking a Cloud ML Engineer (AWS) within Data & Analytics GSL to use ML/AI expertise alongside strong programming and software engineering skills to make machine learning models and analyses easier to use and access. The role supports local markets and group functions to obtain business value from machine learning, and focuses on designing ML systems, productionising prototypes, enabling robust data flows, and evolving Big Data capabilities through reusable assets and patterns.
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.
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 identity, gender expression, sexual orientation, 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.
At Vodafone, we’re working hard to build a better future. A more connected, inclusive and sustainable world. As a dynamic global community, it's our human spirit, together with technology, that empowers us to achieve this.
We challenge and innovate in order to connect people, businesses, and communities across the world. Delighting our customers and earning their loyalty drive us, and we experiment, learn fast and get it done, together.
With us, you can truly be yourself and belong, share inspiration, embrace new opportunities, thrive, and make a real difference.
Apply for Vodafone jobs only through the official Vodafone Careers website to avoid job scams and fraud.
#JDEnhancedByTARA
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Pune, MH, IN
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VOIS Equal Opportunity Employer Commitment 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 identity, gender expression, sexual orientation, 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. Join Us