Job Description :

Required Information Details :

1. Role : AI/ML Engineer

2. Required Technical Skill Set : Python, Generative AI, Langchain, Langraph, AI/ML

3. Desired Experience Range : 6-14 years

4. No of Requirements : 1

5. Location of Requirement : Offshore (Delhi NCR, Chennai, Pune, Bangalore, Hyderabad, Kolkata)

Desired Competencies (Technical/Behavioral Competency) :

Must-Have :

- Experience in developing and deploying GenAI/LLM powered applications/products.

- Experience in building Agentic AI systems, including planning, reasoning, and decision-making components.

- Required proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, transformers, LangChain, LangGraph, Autogen, LLamaIndex etc.).

- Required experience with Natural Language Processing (NLP) techniques, including text generation, understanding, and summarization.

- Proficiency in Python and common ML/NLP libraries (e.g., scikit-learn, spaCy, Hugging Face Transformers).

- Hands-on experience with anomaly detection techniques such as Isolation Forest, One-Class SVM, Autoencoders, or statistical methods.

- Familiarity with NLP tasks such as classification, summarization, and named entity recognition.

- Experience with vectorization techniques (TF-IDF, Word2Vec, BERT, etc.).

- Experience with vector databases (e.g., FAISS, Pinecone, ChromaDB).

- Exposure to LLMs and prompt engineering.

Good-to-Have :

- Preferred experience with prompt engineering and fine-tuning large language models.

- Preferred experience with knowledge graphs and semantic reasoning.

- Preferred experience with multi-agent systems and their coordination.

- Preferred experience with explainable AI (XAI) techniques.

- Preferred experience with MLOps and model deployment pipelines.

- Experience with LangChain or Retrieval-Augmented Generation (RAG) pipelines.

- Familiarity with embedding strategies and chunking techniques.

- Exposure to LLMOps tools and frameworks.

- Understanding of Responsible AI principles and ethical AI development.

Responsibility of / Expectations from the Role :

1. Design and implement machine learning models for anomaly detection in time series and behavioral data.

2. Develop and maintain NLP pipelines for document processing and content generation.

3. Preprocess and clean structured and unstructured data using standard techniques.

4. Implement vectorization techniques and integrate with vector databases (e.g., FAISS, Pinecone, MongoDB Atlas Vector).

5. Work with embedding models (e.g., OpenAI, Hugging Face) to support semantic search and retrieval tasks.

6. Fine-tune and evaluate LLMs for specific use cases such as summarization, classification, and test case generation.

7. Collaborate with backend engineers to expose ML models via APIs.

8. Monitor model performance using metrics like precision, recall, F1 score, and ROC-AUC.

9. Contribute to proof-of-concept projects involving GenAI and RAG architectures.

10. Follow Responsible AI practices in model development and deployment.