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AI / ML Big Data Lead - Cloud Architect
2 months ago
We are seeking a highly skilled and experienced Cloud Big Data Tech Lead to join our team at Vodacom. As a key member of our organization, you will be responsible for leading the design, development, and deployment of AI / ML systems and capabilities.
Key Responsibilities- Lead and shape the design and development of AI / ML systems and capabilities.
- Drive the automation of AI / ML predictive model software, including model training.
- Enable the automation and productionization of data science prototypes through configure-driven capabilities and develop ML apps according to data science requirements.
- Ensure a streamlined, secure, and digitized flow of data in the Group unified lakehouse to enable effective AI / ML model execution and delivery.
- Drive the overall Cloud Big Data architecture and solution design to evolve the Group cloud big data capabilities and components to support business requirements and objectives.
- Stay abreast with the latest trends and research of AI / ML and cloud big data technologies and methods to improve delivery and sustainability of big data, AI / ML applications, and services.
- Make contributions to the process of defining best practice for the agile development of applications to run on the Group cloud big data platform.
- Advanced degree in Computer Science, Math, Statistics, Engineering, or a related field.
- Relevant cloud certification at a professional or associate level.
- 8+ years in Data, AI, and Analytics or related software engineering experience.
- Exposure and experience with delivery of GenAI applications.
- Agile exposure, Kanban, or Scrum.
- Experience managing the development life cycle for agile software development projects.
- Robust software engineering, DevOps engineering, and AI / ML engineering skills and expertise.
- Experience in using a wide range of data tools such as AWS services – S3, SFTP, Glue, EMR (Spark), Step Functions, Athena, CloudWatch, CloudTrail, KMS, SageMaker, Kinesis, OpenSearch, etc.
- Knowledge of Big Data frameworks like Hadoop, Spark, Hive, Yarn, Airflow, etc.
- Experience in working with distributed ML frameworks like H2O and/or TensorFlow.
- Experience in working with various ML libraries with a key focus on AWS Sagemaker.
- Programming experience in Java and Python is essential.
- Experience working with containerization services such as Docker/Kubernetes or cloud alternatives would be an advantage.
- Experience with AWS big data lakehouse architecture & analytics is essential, while working knowledge of GCP would be desirable.
- Experience with other distributed technologies, NoSQL databases, and streaming technologies would be desirable.
- Strong written and verbal communications.
- Excellent interpersonal and collaboration skills.