GenAI & ML Trainee: Enterprise AI & CV RAG (On-site)

RiseWithVishwas; Hinoba-an; On-site; PHP 398,000 - 597,000; Full time

Job summary

L&T Precision Engineering & Systems is seeking a GenAI Trainee at the Powai Innovation Campus to develop end-to-end AI, ML, and computer vision solutions for enterprise and precision engineering domains. You will build and optimize LLM applications with Retrieval-Augmented Generation (RAG), fine-tune models, perform EDA, and deploy high-performance CV pipelines to both cloud platforms and edge devices.

This role offers hands-on experience across PoCs, model benchmarking, and responsible AI

Qualifications

• 0-2 years of experience in GenAI, ML or CV.
• B.Tech or equivalent in a relevant field.
• Strong programming skills in Python and ML frameworks.
• Experience with REST APIs and deploying models to cloud/edge is a plus.

Responsibilities

• Assist in building Generative AI applications, optimizing prompts, and RAG pipelines using LLMs.
• Support the design, training, evaluation, and deployment of ML/CV models (object detection, OCR) using PyTorch, TensorFlow, and OpenCV.
• Clean, preprocess, and engineer features from structured, image, text, and video data.
• Integrate trained AI/ML models into enterprise apps via RESTful APIs, microservices, and cloud/edge deployment.
• Conduct PoCs, model benchmarking, and validations following Responsible AI and safety standards.

Skills

GenAI

ML

Computer Vision

Education

B.Tech

Tools

Python

PyTorch

TensorFlow

OpenCV

REST APIs

Microservices

Git

Job description

L&T Precision Engineering & Systems is seeking a GenAI Trainee at the Powai Innovation Campus to develop end-to-end AI, ML, and computer vision solutions for enterprise and precision engineering domains. You will build and optimize LLM applications with Retrieval-Augmented Generation (RAG), fine-tune models, perform EDA, and deploy high-performance CV pipelines to both cloud platforms and edge devices.

This role offers hands-on experience across PoCs, model benchmarking, and responsible AI