Job Title: Lead / Principal Machine Learning Applied Scientist

Job Location: Gurugram or Chennai (5 Days Work From Office)

Experience Level: 8+ Years

Employment Type: Full time

Department: Artificial Intelligence / Data Science & Analytics

About the Role

We are seeking an experienced and vision-driven Machine Learning Applied Scientist with 8+ years of hands-on experience to lead the development of our next-generation AI architecture. In this role, you will be responsible for designing and deploying end-to-end LLM-driven data processing pipelines, extracting structured insights from complex datasets, and architecting robust knowledge bases to drive intelligent business decisions.

Working on-site from our Gurugram or Chennai offices, you will act as a technical authoritybridging cutting-edge applied AI research with scalable, enterprise-grade execution.

Key Responsibilities

1. LLM Data Processing Pipelines

- Architect, implement, and scale production-ready data pipelines leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques.
- Design robust data orchestration workflows to process large volumes of structured, semi-structured, and unstructured business data with low latency and high accuracy.
- Develop custom evaluation frameworks to monitor LLM performance, benchmark output quality, and minimize hallucinations in automated processing flows.

1. Issue Extraction, Categorization & Pattern Analysis

- Build automated models and prompts to perform high-precision issue extraction, root-cause categorization, and sentiment/intent classification from multi-channel text data.
- Lead deep-dive pattern analysis across unstructured datasets to uncover recurring trends, operational friction points, and actionable business insights.
- Develop statistical and ML models to track the evolution of operational issues over time and alert business leaders to emerging anomalies.

1. Structured Knowledge Base & RAG Systems

- Design and construct enterprise Knowledge Graphs, vector stores,



and structured knowledge repositories optimized for AI retrieval and reasoning.
- Implement retrieval-augmented generation (RAG) strategies, hybrid search, and semantic indexing to ground LLM outputs in verified domain context.
- Establish data ontology and schema standards to ensure knowledge assets remain maintainable, searchable, and secure.

1. Technical Leadership & Cross-Functional Collaboration

- Partner closely with Product, Engineering, and Domain experts to translate complex, ambiguous business problems into clear technical solutions.
- Mentor junior and mid-level data scientists and ML engineers in software engineering best practices, LLM evaluation, and production deployment.

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: Masters 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).

📌 Lead / Principal Machine Learning Applied Scientist (Chennai)
🏢 solve IT consultant
📍 Chennai