Machine Learning Engineer (NLP / Conversational AI)

Triosoft technologies; Bhopal; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Triosoft technologies seeks a Machine Learning Engineer with NLP and Conversational AI expertise to build intelligent AI Voice Agents and Chatbot solutions. You will design, train, evaluate, and deploy intent classification models, NER, and hybrid pipelines combining ML with LLMs.

You will work on data labeling, model training, and production deployment, ensuring performance and scalability while collaborating with cross-functional teams. Prior experience with AI voice bots is a strong advantage.

Qualifications

• Experience with NLP and conversational AI projects.
• Experience building AI Voice Bots or chatbots is a plus.
• Production deployment of ML models and integration with backend services.

Responsibilities

• Design NLP models for Intent Classification and Entity Recognition.
• Prepare, label, and curate conversational datasets.
• Train, evaluate, and deploy ML models for conversational AI.
• Build hybrid AI systems with ML and LLM fallback.
• Develop conversation routing logic using confidence scores.
• Optimize accuracy, latency, and inference performance.
• Integrate ML models with Python backend services and REST APIs.
• Design conversations for AI Voice Bots and Chatbots.
• Work with Prompt Engineering for LLM fallback responses.
• Build and maintain Retrieval-Augmented Generation pipelines.
• Monitor and retrain models as needed.
• Collaborate with Backend, Frontend, and Product teams.

Skills

Python

NLP

Intent Classification

Text Classification

NER

PyTorch

TensorFlow

HuggingFace

Sentence Transformers

REST APIs

Git

Prompt Engineering

RAG

Tools

PyTorch

TensorFlow

HuggingFace

REST APIs

Git

RAG

Job description

Machine Learning Engineer (NLP / Conversational AI)

1-3 Years Experience • 2 Openings • as per industry standards

Job Summary

We are looking for a Machine Learning Engineer with experience in NLP and Conversational AI to build intelligent AI Voice Agents and Chatbot solutions. The candidate will be responsible for designing, training, evaluating, and deploying intent classification models, entity recognition systems, and hybrid AI pipelines combining Machine Learning with Large Language Models (LLMs).

Key Responsibilities

• Design and develop NLP models for Intent Classification and Entity Recognition.
• Prepare, clean, and label conversational datasets.
• Train, fine-tune, and evaluate machine learning models for conversational AI.
• Build hybrid AI systems using ML-based intent detection with LLM fallback.
• Develop conversation routing logic based on confidence scores.
• Optimize model accuracy, latency, and inference performance.
• Integrate ML models with Python backend services and REST APIs.
• Design conversation flows for AI Voice Bots and Chatbots.
• Work with Prompt Engineering for LLM fallback responses.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines.
• Monitor model performance and retrain models when required.
• Collaborate with Backend, Frontend, and Product teams.

Required Skills

• Strong Python programming
• Natural Language Processing (NLP)
• Intent Classification
• Text Classification
• Named Entity Recognition (NER)
• PyTorch or TensorFlow
• Hugging Face Transformers
• Sentence Transformers
• REST APIs
• Git
• Prompt Engineering
• RAG

Good to Have

• Experience building AI Voice Bots
• Conversation Flow Design
• Speech-to-Text (STT) and Text-to-Speech (TTS) integrations
• Production deployment of ML models