ML Data Engineer
Indexed description
Role Summary
The ML Data Engineer is responsible for designing, developing, and supporting scalable data and AI platforms that enable machine learning, advanced analytics, and intelligent applications across the enterprise. This role focuses on building robust data pipelines, integrating structured and unstructured data sources, and supporting AI/ML solutions in cloud-based environments.
What You'll Do And How You'll Make Your Mark
- Developing API-based ingestion frameworks, event-streaming solutions, real-time and batch data pipelines, and optimizing large-scale data processing environments.
- Supports emerging AI technologies such as embeddings, vector databases, retrieval-augmented generation (RAG), and AI-driven application integration.
- Partners closely with data engineering, BI, analytics, application, and AI teams to ensure enterprise data is reliable, governed, scalable, and optimized for both reporting and AI-driven use cases.
- Strong experience with cloud data platforms, distributed data processing, SQL and Python development, and modern data architecture patterns.
- Experience with OCI, AWS, or GCP environments, as well as exposure to AI/ML operationalization and MLOps concepts, is highly desirable.
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