AI/ML – Gen AI

Job Title : AI/ML – Gen AI

Exp : 9-10 yrs

Location : Bangalore, Chennai, Hyderabad, Noida, Pune, Trivandrum

About The Role

We are seeking a hands-on, highly experienced AI engineer with deep expertise in LLMs,

Retrieval-Augmented Generation (RAG), fine-tuning, and applied machine learning.

You will help build next-generation investor relations and public relations tools powered by

AI, including intelligent assistants, content generation, semantic search, and predictive

analytics.

Machine Learning + Deep Learning + Generative AI

Key Responsibilities

 Design and implement RAG pipelines that combine proprietary data (e.g., press

releases, earnings transcripts) with LLMs to generate accurate, secure outputs.

 Fine-tune open-source LLMs (e.g., LLaMA 2/3, Mistral, Mixtral) using instruction or

LoRA-based methods for specific use cases such as branded content generation or

question-answering.

 Build and optimize embeddings, Vector search algorithms proficenecy e.g. HNSW,

FAISS, IVFFlat and Microsoft -> Semantic Kernel and semantic retrieval systems

using tools like sentence-transformers, FAISS, Weaviate, or Pinecone.

 Collaborate with product and content teams to implement intelligent Q&A, press

release graders, interview prep tools, and performance analysis assistants.

 Develop traditional ML models for anomaly detection, time-series forecasting, and

engagement optimization (Prophet, XGBoost, scikit-learn, Chronos, ARIMA,

Microsoft -> Semantic Kernel etc.).

 Integrate multimodal components such as TTS (e.g., ElevenLabs), image

recommendation, and social publishing automation.

 Deep Learning in Neural Networks.

 Hands on experience in Tensorflow, Pytorch.

 Ensure secure and scalable deployment of AI systems (on cloud AWS, AWS

Bedrock, AWS SegemakerAzure OpenAI, or in-house GPU infrastructure).

Qualifications

 5+ years of hands-on experience in ML/AI engineering or applied data science

 Proven experience with LLMs (GPT-4, Claude, LLaMA, Mistral, etc.) and RAG

architectures

 Strong coding skills in Python and experience with LangChain, Hugging Face

Transformers, OpenAI API, PEFT/LoRA.

 Experience fine-tuning LLMs using open-source frameworks and adapting models

with domain-specific data

 Deep understanding of NLP, search, and vector-based retrieval systems

 Experience with time-series modeling, anomaly detection, or ML classification

tasks

 Familiarity with DevOps or MLOps tooling for deploying and monitoring LLM-powered

applications

 Excellent communication skills and ability to work cross-functionally with product,

content, and engineering teams

Preferred

 Experience in financial, PR, or media domains

 Familiarity with embedding alignment, model evaluation, and prompt

engineering

 Comfortable working with both cloud APIs (e.g., OpenAI, Azure, Anthropic) and

open-source LLMs

Good To Have

Postgressql vector db for embeddings, azure open ai services and c# .net 9 framework for

building all business logic and services for our enterprise applications.