Machine Learning Engineer (NLP/Chatbots)

Stackbinary; Mumbai; Hybrid; INR 2,400,000 - 4,200,000; Full time

Benefits offered by this job

Flexible working hours

Remote-friendly culture

Learning & development budget

High-ownership projects

Pragmatic engineering culture

Work with cutting-edge tech

Job summary

StackBinary in Mumbai, India, is seeking an ML engineer to build NLP models, deploy RAG systems, and develop conversational AI solutions. You will work with LLMs, optimize performance, and design evaluation frameworks for dialogue systems.

Ideal candidates have 4+ years of NLP ML experience, strong Python skills, and hands-on experience with PyTorch/TensorFlow, vector databases, and cloud ML platforms. Collaboration with product teams and scalable data pipelines are core to the role.

Qualifications

• 4+ years of ML/NLP engineering experience.
• Strong Python programming skills.
• Hands-on experience with transformer models and large language models.
• Knowledge of vector databases and semantic search.
• Understanding of MLOps practices and model deployment.
• Experience with cloud ML platforms (SageMaker, Vertex AI).
• Strong background in statistics and ML theory.

Responsibilities

• Design and implement RAG (Retrieval-Augmented Generation) systems
• Build and fine-tune LLMs for specific use cases
• Develop chatbot architectures and conversation flows
• Implement model evaluation and monitoring frameworks
• Optimize model performance and reduce inference costs
• Create data pipelines for training and inference
• Collaborate with product teams on AI feature requirements

Skills

NLP engineering

Python

LLMs/Transformers

MLOps

Statistics

Cloud platforms

Tools

PyTorch

TensorFlow

SageMaker

Vertex AI

Vector databases

Job description

About The Role

Build and deploy NLP models and chatbot systems. You'll work with LLMs, implement RAG architectures, and create evaluation frameworks for conversational AI systems.

What You’ll Do

• Design and implement RAG (Retrieval-Augmented Generation) systems
• Build and fine-tune LLMs for specific use cases
• Develop chatbot architectures and conversation flows
• Implement model evaluation and monitoring frameworks
• Optimize model performance and reduce inference costs
• Create data pipelines for training and inference
• Collaborate with product teams on AI feature requirements

What You’ll Bring

• 4+ years of ML engineering experience with focus on NLP
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
• Experience with transformer models and large language models
• Knowledge of vector databases and semantic search
• Understanding of MLOps practices and model deployment
• Experience with cloud ML platforms (SageMaker, Vertex AI)
• Strong background in statistics and machine learning theory

Nice to Have

• Experience with prompt engineering and fine-tuning techniques
• Knowledge of multi-modal models (vision + language)
• Familiarity with reinforcement learning from human feedback (RLHF)
• Understanding of distributed training and model parallelism

What You’d Build

• AI Call Center & AI Receptionist - Voice AI that answers business calls in 11 languages and logs every conversation.
• Sales Intelligence Engine - Finds companies, people and numbers, then tells reps what to pitch.

Why Join StackBinary

• Flexible working hours
• Remote-friendly culture
• Learning & development budget
• High-ownership projects
• Pragmatic engineering culture
• Work with cutting-edge tech