L&T Recruitment 2026 | GenAI Trainee | B.Tech/M.Tech

Job Overview

Role: GenAI Trainee Location: Mumbai Experience: 0-2 Years Qualification: B.Tech/M.Tech Key Skills: Machine Learning, Deep Learning, Generative AI, LLMs, Computer Vision

Job Description

Larsen & Toubro (L&T) is hiring for the position of GenAI Trainee under its DEIC-L&T Precision Engineering & Systems IC. The L&T Recruitment 2026 opportunity is available at the L&T Innovation Campus, Powai, Mumbai . Candidates with B.Tech or M.Tech qualifications and 0–2 years of experience can apply. The role provides exposure to Machine Learning, Deep Learning, Generative AI, Large Language Models, Retrieval-Augmented Generation (RAG), Computer Vision, data analytics, AI application development, and cloud-based AI solutions. As an emerging technology role, the GenAI Trainee will be expected to stay updated with developments in AI and contribute to documentation and compliance activities.

Roles and Responsibilities

• ML & AI Solution Development: Assist in developing and evaluating Machine Learning and Artificial Intelligence solutions. Collecting, cleansing, preprocessing, and validating structured and unstructured datasets. Supporting the design, development, training, and evaluation of machine learning and deep learning models. Performing feature engineering and model tuning. Supporting model performance optimization. Conducting model validation, testing, benchmarking, and documentation. Assisting with deployment and monitoring of AI/ML models. Analyzing model performance and recommending improvements.
• Generative AI Development: Developing applications using Large Language Models. Working with multimodal AI models. Prompt engineering and prompt optimization. Evaluating LLM responses. Working on Retrieval-Augmented Generation (RAG) solutions. Supporting fine-tuning and model customization projects. Developing and testing AI-powered chatbots and virtual assistants. Developing content-generation solutions. Evaluating AI outputs for quality, factual accuracy, safety, and compliance. Integrating Generative AI capabilities into enterprise applications through APIs and frameworks.
• Computer Vision: Developing image and video analytics solutions. Supporting object detection and image classification models. Working with image segmentation and object tracking. Supporting OCR-based solutions. Preparing and preprocessing image and video datasets. Working with data annotation, labeling, and augmentation. Using frameworks such as OpenCV, TensorFlow, PyTorch, and YOLO. Training and evaluating computer vision models. Supporting deployment and optimization of vision models. Performing accuracy and quality analysis of computer vision systems.
• Data Analytics & Engineering: Performing Exploratory Data Analysis (EDA). Analyzing large datasets and identifying useful insights. Creating visualizations, reports, and dashboards. Supporting data pipelines and workflows for AI applications. Maintaining data quality and integrity. Following data governance practices. Processing image, text, audio, and video datasets.
• AI Solution Integration: Support intelligent automation and AI-driven business solutions. Integrate AI, Generative AI, and Computer Vision models with applications. Work with web, mobile, and enterprise applications. Assist in developing APIs and microservices. Support cloud-based AI solutions. Participate in software testing and debugging. Troubleshoot AI application issues. Follow coding standards and software development best practices. Use version control systems as part of software development activities.
• Research & Innovation: Researching advancements in Artificial Intelligence. Learning new Machine Learning and Deep Learning techniques. Exploring Generative AI technologies. Researching Computer Vision developments. Developing proof-of-concept (PoC) solutions. Evaluating new AI frameworks, tools, and platforms. Contributing ideas for AI products and services. Participating in technical discussions and innovation initiatives. Participating in hackathons where applicable.
• Documentation & Responsible AI: Preparing technical documentation. Documenting datasets and data-processing procedures. Documenting model training and evaluation procedures. Preparing project reports. Following Responsible AI principles. Following cybersecurity and data privacy requirements. Following ethical AI guidelines. Supporting compliance with organizational and industry standards.
• Collaboration & Learning: Work with AI Engineers, Data Scientists, Software Developers, Product Teams, Business Stakeholders. Participate in Agile ceremonies, code reviews, technical meetings, training, mentoring, and self-learning activities.

Skills and Eligibility Criteria

Educational Background: B.Tech qualification. M.Tech qualification.

Experience: 0–2 years of experience.

Mandatory Technical Skills:

• Machine Learning
• Artificial Intelligence
• Deep Learning
• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Prompt Engineering
• Computer Vision
• OpenCV, TensorFlow, PyTorch, YOLO (frameworks)
• OCR
• APIs, Microservices
• Cloud-based AI solutions

Competencies:

• Strong analytical and problem-solving skills
• Willingness to learn emerging technologies