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Tier-1 brand, Bangalore metro, popular ML role and broad required skills increase competitiveness.
Core ML, data engineering and LLM skills are broadly transferable across industries.
Mandatory 7+ years and extensive ML, data pipeline, and GenAI technology requirements raise filter strictness.
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Develop, maintain, and optimize scalable data pipelines and workflows, including feature stores, for AI-driven support and service experiences.
Implement AI/ML solutions such as anomaly detection, text data extraction/summarization using LLMs, and sensitive data redaction with Gen AI and NLP techniques.
Integrate data from diverse sources using AWS S3 and Snowflake; automate observability and build AI applications interacting with MCP servers.
7+ years of data analysis and AI/ML engineering experience.
Bachelor’s degree in computer science, statistics, informatics, information systems, or a quantitative field.
Proficiency in Python, Pyspark, SQL, ETL/ELT data transformation, and experience with web crawling and APIs (e.g., Salesforce API).
Experience with handling semi/unstructured data, AI/ML techniques, LLMs, vector databases, NLP, and using AWS services such as S3; familiarity with Snowflake or SQL data warehouses.
Experienced in building end-to-end AI/ML data pipelines for semi/unstructured and structured data at scale in cloud environments.
Skilled in modern NLP, Gen AI, large language models, and AI application development within complex technical ecosystems (e.g., MCP servers).
Capable of driving automation, observability, and data governance initiatives with attention to data accuracy, security, and compliance.