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Ai Ml Engineer

Posted on July 2, 2026

Ka, India
0 - 0 USD (yearly)

Full Time

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Title: AI-ML Engineer

What are my responsibilities?

As an AI-ML Engineer, you are required to:

Analyze structured and unstructured data sources to understand data lineage, identify relevant datasets, and support reliable data retrieval for downstream applications and analytical workflows.
Work on data-driven solutions using Python, including data processing, transformation, analysis, and document/content generation workflows where required.
Apply AI/ML techniques and modern models to improve data understanding, content extraction, enrichment, classification, and generation use cases.
Collaborate with engineering and business teams to identify the right data sources, tables, columns, and transformation logic needed to enable scalable and accurate solutions.
Contribute to the design and support of backend services and APIs for data-centric applications; familiarity with cloud-native and API-based architectures is an advantage.
Support solutions that enable intelligent data identification and retrieval across diverse sources, including search-oriented approaches, semantic retrieval, and metadata-driven discovery patterns.

Qualification: Bachelor's or Master's in Computer Science & Engineering, Data Engineering, Data Science, Artificial Intelligence, Software Engineering, or equivalent.

Experience level: At least 3 - 5 years of hands-on experience in data engineering, data analysis, machine learning applications, with strong practical exposure to Python and SQL-based data retrieval.

Desired Knowledge & Experience:

Strong hands-on experience in data transformation, data analysis, data quality, data profiling, and source-to-target mapping.
?Strong knowledge of enterprise data platforms and databases, including schema understanding, data lineage tracing, and structured/unstructured data analysis.
?Strong SQL skills and practical experience identifying the right tables, columns, joins, and transformation logic needed to retrieve and prepare business data.
?Hands-on expertise with Python is a must, including its use for data processing, analytics, automation, and integration of AI/ML models with data-driven workflows.
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Knowledge of cloud technologies and frameworks in Microsoft Azure is preferred.
Well-versed in relational database design and experience with processing and managing large data sets (multiple TB scale). (e.g. T-SQL, Microsoft SQL, Oracle)

Good know-how & experience on Dataops (Data Orchestration / Workflow management & Monitoring Systems) and suggest improvements / inputs for CI/CD.

Knowledge of Azure cloud-based data storage and services is preferred.

Familiarity with FastAPI or similar API frameworks is preferred.

Familiarity with semantic search, vector databases, or search/indexing technologies for efficient data identification and retrieval.
Experience in working with LLMs, Agentic AI solutions

Experience in working with Knowledge Graph, Ontology Representation – desirable.

Experience integrating data from multiple enterprise and external sources, and building applications or services that orchestrate retrieval, enrichment, and generation workflows, is a strong advantage.

Exposure to modern interoperability patterns such as model context integrations, connector services, or server-based orchestration for AI/data applications is desirable.