AI ML Engineer

Whiteblue; Chennai; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

A technology company in Chennai is looking for an AI Engineer to design and deliver AI solutions for real-world challenges. The ideal candidate will have 5-8 years of experience, strong skills in Python and Machine Learning, as well as a solid understanding of NLP techniques. You will work in-office from 9:30 AM to 6:30 PM IST, focusing on developing AI systems that can reason and interact with data effectively.

Qualifications

• 5-8 years of experience in AI design and implementation.
• Strong experience in Python and/or PyTorch.
• Hands-on experience with CNNs and LSTMs.

Responsibilities

• Design and implement applied AI solutions for engineering and system problems.
• Build AI systems that can reason, plan, and interact with tools.
• Develop and transition PoCs into usable tools.

Skills

Python

PyTorch

Machine Learning

Deep Learning

NLP Techniques

Transformers

Embeddings

Language Models

CNNs

LSTMs

Job description

Design and deliver applied AI solutions for real-world problems, including building agentic AI systems that can reason, plan, and interact with tools.

Employment Type: Full Time

Timing: 9:30 AM to 6:30 PM IST

Work Mode: Work From Office

Experience: 5-8 years

Key Responsibilities

• Design and implement Applied AI solutions for real-world engineering and system problems.
• Build agentic AI systems that can reason, plan, and interact with tools and data.
• Develop PoCs to validate AI use cases and rapidly transition successful PoCs into usable tools.
• Create AI-powered tools to improve productivity of engineering and product teams.
• Design and implement RAG (Retrieval-Augmented Generation) systems using structured and unstructured data.
• Build feedback and evaluation systems to continuously improve AI performance.

Required Skills & Qualifications

• Strong experience in Python and/or PyTorch.
• Solid understanding of conventional Machine Learning and Deep Learning.
• Strong knowledge of NLP techniques, transformers, embeddings, and language models.
• Hands‑on experience with CNNs and LSTMs.
• Experience with fine‑tuning models (LLMs or task‑specific models).
• Experience building and operating RAG systems.
• Ability to design end‑to‑end AI pipelines, from data ingestion to inference.