Role & responsibilities
Develop product matching and entity resolution solutions using ML and data engineering.
Implement semantic search, vector embeddings, and fuzzy matching techniques.
Contribute to retrieval-augmented generation (RAG) workflows for product enrichment.
Build data pipelines and optimize ML workflows in Snowflake, Databricks, AWS, Azure, or GCP.
Collaborate with product teams and domain experts to deliver AI-driven solutions.
Preferred candidate profile
Robust programming in Python and SQL.
Hands-on with embeddings, vector search, semantic retrieval.
Experience with cloud-native data platforms.
Knowledge of fuzzy matching algorithms (Levenshtein, Jaro-Winkler, Soundex, etc.).
Understanding of LLMs, Generative AI, RAG.
📌 Machine Learning / Data Engineer Chennai (India)
🏢 Cynosure Corporate Solutions
📍 India
Reply to this offer
Impress this employer describing Your skills and abilities, fill out the form below and leave Your personal touch in the presentation letter.