Ai Ml Engineer

Navayuvabharat Infotech; Nagpur District, Pune District, Mumbai; Hybrid; INR 1,200,000 - 2,100,000; Part time

Job summary

Navayuvabharat Infotech is seeking an experienced AI/ML Engineer / AI Scientist for a C2H engagement. Hybrid work mode with onsite locations across major cities. 5–8 years of hands-on experience in ML, DL, NLP/CV, and GenAI needed to drive real-world business AI solutions.

You will build, deploy and support production-grade AI/ML systems, leveraging RAG, Transformer models and MLOps practices to deliver scalable outcomes.

Qualifications

• 5–8 years of professional experience in AI/ML.
• Hands-on experience building and deploying production AI/ML solutions.
• Experience with Generative AI and MLOps lifecycle.

Responsibilities

• Develop, deploy and support AI/ML and GenAI solutions in production environments.
• Collaborate to translate business problems into ML solutions and measurable outcomes.
• Evaluate and optimize models, pipelines, and performance in real-world scenarios.

Skills

Machine Learning

Deep Learning

Generative AI

NLP

Computer Vision

CNN/RNN/Transformers

MLOps

Cloud & Cloud Security

Model Deployment

RAG/Agentic AI

Agentic Workflows

Graph RAG

Tools

TensorFlow

PyTorch

LLMs

XGBoost

Job description

AI/ML Engineer C2H

Experience:5 to 8 Years
Employment Type: C2H (Contract-to-Hire)
Work Mode: Hybrid 3 Days/Week
Locations: Pune, Mumbai, Nagpur, Indore, Noida, Gurgaon, Goa, Jaipur, Ahmedabad, Bangalore, Hyderabad, Kolkata

Role Overview

We are looking for an experienced AI/ML Engineer / AI Scientist with strong hands-on experience in Machine Learning, Deep Learning, Generative AI and MLOps.

Key Skills

• Machine Learning & Deep Learning
• NLP and/or Computer Vision
• CNN, RNN & Transformer models
• ML algorithms Regression, Random Forest, SVM, XGBoost
• Generative AI / LLMs
• RAG, Agentic AI & Agentic Workflows
• Graph RAG & Model Tuning
• MLOps & ML Model Deployment
• Cloud & Cloud Security
• Experience building and deploying AI/ML solutions in production

What We Need

Candidates should have strong hands-on experience developing, deploying and supporting AI/ML and GenAI solutions and should be able to apply ML techniques to real-world business problems.