Requirements & Qualifications

● Experience: 8+ years of professional experience in Applied Machine Learning, NLP, and

Data Science, with at least 2+ years focused on LLM architectures and production

pipelines.

● Education: Master’s or Ph.D. in Computer Science, Data Science, Statistics,

Mathematics, or a related quantitative field.

● Core Technical Expertise:

○ LLMs & Generative AI: Deep expertise in fine-tuning, prompt engineering, RAG

pipelines, agentic workflows, and frameworks like LangChain, LlamaIndex, or

AutoGen.

○ Vector Databases & Search: Hands-on experience with vector stores (e.g.,

Pinecone, Milvus, Qdrant, Chroma) and hybrid search implementations (BM25 +

Dense Retrieval).

○ NLP & Text Analytics: Proven mastery in named entity recognition (NER), issue

extraction, text classification, semantic clustering, and topic modeling.

○ Programming & Systems: Expert-level Python proficiency along with standard ML

frameworks (PyTorch, Hugging Face, Scikit-learn) and big-data processing tools

(Spark, SQL).

● Location & Work Mode: Willingness to work 5 days from office at either our Gurugram or

Chennai location.

Preferred Qualifications

● Track record of deploying scalable LLM applications in enterprise production

environments.

● Experience with knowledge graph technologies (Neo4j, RDF, SPARQL) and automated

ontology building.

● Familiarity with MLOps frameworks, CI/CD pipelines for AI, and cloud infrastructure

(AWS, Azure, or GCP).

Requirements & Qualifications

● Experience: 8+ years of professional experience in Applied Machine Learning, NLP, and

Data Science, with at least 2+ years focused on LLM architectures and production

pipelines.

● Education: Master’s or Ph.D. in Computer Science, Data Science, Statistics,

Mathematics, or a related quantitative field.

● Core Technical Expertise:

○ LLMs & Generative AI: Deep expertise in fine-tuning, prompt engineering, RAG

pipelines, agentic workflows, and frameworks like LangChain, LlamaIndex, or

AutoGen.

○ Vector Databases & Search: Hands-on experience with vector stores (e.g.,

Pinecone, Milvus, Qdrant, Chroma) and hybrid search implementations (BM25 +

Dense Retrieval).

○ NLP & Text Analytics: Proven mastery in named entity recognition (NER), issue

extraction, text classification, semantic clustering, and topic modeling.

○ Programming & Systems: Expert-level Python proficiency along with standard ML

frameworks (PyTorch, Hugging Face, Scikit-learn) and big-data processing tools

(Spark, SQL).

● Location & Work Mode: Willingness to work 5 days from office at either our Gurugram or

Chennai location.

Preferred Qualifications

● Track record of deploying scalable LLM applications in enterprise production

environments.

● Experience with knowledge graph technologies (Neo4j, RDF, SPARQL) and automated

ontology building.

● Familiarity with MLOps frameworks, CI/CD pipelines for AI, and cloud infrastructure

(AWS, Azure, or GCP).