ML/AI Engineer

GAVS Technologies N.A., Inc; Pune District; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

GAVS Technologies N.A., Inc in Pune is seeking an ML/AI Engineer with 4–5 years experience to design, build, and deploy intelligent agents and ML solutions powering our platform.

You will work with Python, LLMs, multi-agent frameworks, and RAG pipelines, ensuring scalable data processing, model evaluation, and observability.

Collaborate with frontend and backend teams to integrate AI services and contribute to documentation.

Qualifications

• Strong Python programming skills.
• Hands-on experience with NLP/ML and LLMs.
• Experience with multi-agent frameworks and orchestration.
• Knowledge of Retrieval Augmented Generation (RAG) pipelines.
• Familiarity with ML/NLP libraries such as Pandas and NumPy.

Responsibilities

• Design, develop, and implement AI agents using modern multi-agent frameworks (e.g., CrewAI, LangChain, LangGraph, or similar).
• Build and deploy NLP models and Large Language Models (LLMs) for QA, summarization, and topic prediction.
• Develop RAG pipelines for knowledge retrieval, reasoning, and explainability.
• Implement model evaluation and monitoring strategies to ensure reliability and accuracy of LLM-based systems.
• Build and maintain scalable data processing and normalization pipelines.
• Collaborate with frontend and backend engineers to integrate AI services into the product.
• Contribute to observability and monitoring using tools such as Prometheus, Jaeger, Kibana.
• Participate in code reviews, testing, and technical documentation.

Skills

Python

LLMs

Prompt engineering

Multi-agent systems

API development

Cloud basics

Observability

Tools

Pandas

NumPy

LlamaIndex

LangChain

LangGraph

CrewAI

Prometheus

Jaeger

Kibana

Job description

Job Title: ML/AI EngineerWe are building an innovative, agent-driven AI/ML platform designed to support structured financial conversations between customers and intelligent assistants. The system leverages advanced machine learning and natural language technologies to translate diverse customer inputs into actionable financial insights and deliver outcomes across multiple surfaces.We are looking for a talented ML/AI Engineer (4–5 years of experience) to join our team and help design, build, and deploy intelligent agents and machine learning solutions that power this platform.

Responsibilities

• Design, develop, and implement AI agents using modern multi-agent frameworks (e.g., CrewAI, LangChain, LangGraph, or similar).
• Build and deploy Natural Language Processing (NLP) models and Large Language Models (LLMs) for tasks such as Q&A, summarization, and topic prediction.
• Develop Retrieval Augmented Generation (RAG) pipelines for knowledge retrieval, reasoning, and explainability.
• Implement model evaluation and monitoring strategies to ensure reliability and accuracy of LLM-based systems.
• Build and maintain scalable data processing and normalization pipelines.
• Collaborate with frontend and backend engineers to integrate AI services seamlessly into the overall product.
• Contribute to observability and monitoring efforts using tools such as Prometheus, Jaeger, Kibana, or equivalent.
• Participate in code reviews, testing, and technical documentation.

Required Skills

• Strong programming skills in Python.
• Practical experience with Large Language Models (LLMs), including prompt engineering and fine-tuning.
• Experience with multi-agent systems and orchestration frameworks (CrewAI, LangChain, LangGraph, or similar).
• Knowledge of Retrieval Augmented Generation (RAG) using tools such as LlamaIndex, LangChain, etc.
• Hands-on experience in Machine Learning (ML) and Natural Language Processing (NLP).
• Proficiency with data processing libraries (e.g., Pandas, NumPy).
• Understanding of API development and integration.
• Basic knowledge of cloud platforms and deployment concepts.
• Experience with monitoring and observability tools (e.g., Prometheus, Jaeger, Kibana).
• Ability to work collaboratively in a cross-functional team.

Preferred / Good-to-Have Skills

• Experience with MLOps practices for deploying, monitoring, and scaling models.
• Familiarity with financial domain applications or conversational AI systems.
• Exposure to time-series forecasting methods.