TL;DR

Staff Engineer (Machine Learning): Design, develop, and deploy machine learning models and GenAI solutions for BFSI use cases with an accent on LLM architecture, fine-tuning, and RAG systems. Focus on building production-ready ML systems, scalable APIs, conversational AI workflows, and ensuring model governance and compliance.

Company

%hirify_global% is a global digital product engineering company with over 17,500 experts across 39 countries, focused on building inspiring products, services, and experiences.

What you will do

Design, develop, and deploy ML models for BFSI use cases like credit scoring, fraud detection, and churn prediction.
Build GenAI and NLP solutions using Python, PyTorch, TensorFlow, Hugging Face, and LangChain.
Develop LLM-based applications including fine-tuning and RAG pipelines with vector databases.
Implement MLOps pipelines using CI/CD, MLflow, Docker, and Kubernetes.
Build scalable REST/GraphQL APIs using FastAPI, Flask, or similar frameworks.
Design and deploy conversational AI workflows using Dialogflow, Rasa, or Microsoft Bot Framework.

Requirements

6+ years of hands-on experience in Machine Learning / AI Engineering.
Proven delivery experience in BFSI, especially in GenAI solutions.
Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face.
Deep understanding of LLM architecture, transformers, embeddings, tokenization.
Experience with LLM fine-tuning: LoRA, PEFT, prompt tuning.
Experience building RAG systems with Pinecone, FAISS, Weaviate, Chroma.

Culture & Benefits

Dynamic and non-hierarchical work culture.
Global presence with experts across 39 countries.
Focus on inspiring and exciting digital product engineering.