Machine Learning Engineer (NLP / Conversational AI)

Triosoft Technologies Pvt. Ltd.; Bhopal; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Triosoft Technologies Pvt. Ltd. in India seeks a Machine Learning Engineer (NLP / Conversational AI) to design, train, and deploy NLP models for intent classification and NER within conversational agents.

You will build hybrid AI pipelines with LLMs, craft conversation flows, and optimize accuracy, latency, and inference performance. The role requires strong Python, experience with PyTorch or TensorFlow, Hugging Face Transformers, Sentence Transformers, REST APIs, Git, and prompt engineering.

Qualifications

• Strong Python programming skills and experience in NLP workflows.
• Proven ability to build intent classification and entity recognition models.
• Experience with PyTorch or TensorFlow and Hugging Face Transformers.
• Familiarity with REST APIs and version control (Git).
• Hands-on with RAG pipelines and LLM integration.

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.

Skills

Python

NLP

Intent Classification

Text Classification

Named Entity Recognition

PyTorch or TensorFlow

Hugging Face Transformers

Sentence Transformers

REST APIs

Git

Prompt Engineering

RAG

Tools

PyTorch or TensorFlow

Hugging Face Transformers

Job description

Machine Learning Engineer (NLP / Conversational AI)

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