L&T GenAI Trainee Recruitment 2026 – Freshers | Powai

Published on: September 23, 2026
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L&T GenAI Trainee Recruitment 2026 – Freshers | Powai

L&T GenAI Trainee Recruitment 2026: Larsen & Toubro (L&T) is hiring candidates for the GenAI Trainee position under DEIC – L&T Precision Engineering & Systems IC in Powai. The role is suitable for candidates with 0–2 years of experience who have a strong interest in Artificial Intelligence, Machine Learning, Generative AI, Computer Vision, and Data Analytics.

This position provides an opportunity to work on AI-driven solutions involving Large Language Models (LLMs), RAG, deep learning, computer vision, AI applications, and enterprise AI integration.

Job Overview

Job Details Information
Company Larsen & Toubro (L&T)
Job Role GenAI Trainee
Job ID LNT/GT/1820559
Business Unit DEIC – L&T Precision Engineering & Systems IC
Location Powai
Experience 0–2 Years
Qualification Bachelor of Technology (B.Tech)
Required Skills Machine Learning, Artificial Intelligence
Posted On 13 August 2026
Application End Date 09 February 2027

About the Role

The GenAI Trainee role focuses on developing and supporting AI and machine learning solutions. Selected candidates can gain hands-on exposure to multiple areas of modern AI, including:

  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models
  • Retrieval-Augmented Generation (RAG)
  • Computer Vision
  • Data Analytics
  • AI application development
  • Cloud-based AI solutions

The role also involves collaborating with AI engineers, data scientists, software developers, product teams, and business stakeholders.

Machine Learning & AI Responsibilities

Candidates will assist with activities such as:

  • Collecting and preprocessing structured and unstructured datasets
  • Data cleansing and validation
  • Developing and evaluating machine learning and deep learning models
  • Feature engineering
  • Model tuning and optimization
  • Model testing and benchmarking
  • Model documentation
  • Deployment and monitoring of AI/ML models
  • Analyzing model performance and identifying improvements

Generative AI Responsibilities

The role provides exposure to Generative AI and LLM-based applications.

Candidates may work on:

  • Large Language Model applications
  • Prompt engineering
  • Prompt optimization
  • Response evaluation
  • Retrieval-Augmented Generation (RAG)
  • Fine-tuning and model customization
  • AI-powered chatbots
  • Virtual assistants
  • Content generation solutions
  • LLM API integration
  • Enterprise Generative AI applications

Candidates will also evaluate AI outputs for quality, factual accuracy, safety, and Responsible AI compliance.

Computer Vision

The position also includes computer vision-related work such as:

  • Object detection
  • Image classification
  • Image segmentation
  • Object tracking
  • OCR
  • Image and video processing
  • Dataset annotation and labeling
  • Data augmentation
  • Computer vision model training and evaluation

Candidates may work with technologies and frameworks such as OpenCV, TensorFlow, PyTorch, and YOLO.

Data Analytics & Engineering

The GenAI Trainee may also support data analytics and engineering activities, including:

  • Exploratory Data Analysis (EDA)
  • Data visualization
  • Creating reports and dashboards
  • Building data pipelines
  • Data quality and governance
  • Processing text, image, audio, and video datasets
  • Generating insights from large datasets

AI Solution Development

Selected candidates can also participate in developing and integrating AI-powered solutions.

Responsibilities may include:

  • Building intelligent automation solutions
  • Integrating AI models with web and mobile applications
  • Enterprise application integration
  • Developing APIs and microservices
  • Cloud-based AI solutions
  • Software testing and debugging
  • Troubleshooting AI applications
  • Following coding and version-control practices

Research & Innovation

Candidates will be encouraged to stay updated with developments in:

  • Artificial Intelligence
  • Machine Learning
  • Generative AI
  • Deep Learning
  • Computer Vision
  • AI frameworks and platforms

The role may involve developing Proofs of Concept (PoCs), evaluating emerging AI technologies, participating in hackathons, and contributing ideas for new AI products and solutions.

Documentation & Compliance

Candidates will also be expected to support:

  • Technical documentation
  • Model documentation
  • Dataset documentation
  • Training procedure documentation
  • Model evaluation reports
  • Deployment documentation
  • Responsible AI practices
  • Cybersecurity and data privacy requirements
  • Ethical AI guidelines

Eligibility Criteria

The listed minimum qualification is:

  • Bachelor of Technology (B.Tech)
  • Experience: 0–2 years
  • Knowledge of Machine Learning and Artificial Intelligence

Candidates with academic projects, internships, personal projects, or practical experience in AI/ML and Generative AI can highlight those projects in their resumes.

Key Skills

Important areas relevant to this position include:

  • Machine Learning
  • Artificial Intelligence
  • Deep Learning
  • Generative AI
  • LLMs
  • Prompt Engineering
  • RAG
  • Python/programming
  • Computer Vision
  • OpenCV
  • TensorFlow
  • PyTorch
  • YOLO
  • Data Analytics
  • APIs
  • Cloud AI
  • Data preprocessing
  • Model evaluation

Collaboration & Learning

The trainee will work with multidisciplinary teams including:

  • AI Engineers
  • Data Scientists
  • Software Developers
  • Product Teams
  • Business Stakeholders

The role also involves participation in Agile ceremonies, code reviews, technical discussions, training, mentoring, and continuous learning.

How to Prepare for the Role?

Candidates interested in this opportunity can strengthen their profiles by working on projects involving:

  1. Machine Learning – Build and evaluate basic ML models.
  2. Generative AI – Create an LLM-powered application.
  3. RAG – Build a document-based question-answering system.
  4. Computer Vision – Develop an object detection or image classification project.
  5. Python & Data – Practice data preprocessing, EDA, and visualization.
  6. Git/GitHub – Maintain a portfolio of AI projects.

Selection Process

The exact selection process may vary based on L&T’s recruitment requirements. Candidates may be evaluated through a combination of:

  1. Application screening
  2. Technical assessment
  3. Technical interview
  4. HR/interview discussion
  5. Final selection

Candidates should keep an updated resume highlighting relevant AI/ML projects and technical skills.

Important Details

  • Company: Larsen & Toubro (L&T)
  • Position: GenAI Trainee
  • Job ID: LNT/GT/1820559
  • Location: Powai
  • Experience: 0–2 years
  • Qualification: B.Tech
  • Skills: Machine Learning, Artificial Intelligence
  • Posted: 13 August 2026
  • End Date: 09 February 2027

How to Apply?

Interested candidates should visit the official L&T careers portal and search for GenAI Trainee – LNT/GT/1820559 to submit their application.

Candidates should ensure that their resume clearly mentions relevant AI/ML, Generative AI, Computer Vision, Python, data analytics, and project experience before applying.

How to Apply for L&T GenAI Trainee

  1. Visit the official L&T Careers website and search for GenAI Trainee – LNT/GT/1820559.
  2. Check the eligibility criteria — B.Tech qualification with 0–2 years of experience and knowledge of AI/ML.
  3. Click on the Apply button and register/login to the L&T careers portal.
  4. Fill in your personal, educational, and professional details and upload your updated resume.
  5. Submit the application and keep your application/reference details for future communication.
  6. 📌Apply Now

Conclusion

The L&T GenAI Trainee Recruitment 2026 offers an opportunity for B.Tech graduates and early-career candidates to work across several emerging technology areas, including Generative AI, Machine Learning, LLMs, RAG, Computer Vision, Data Analytics, and AI application development.

Candidates with a strong interest in AI and hands-on project experience can use this opportunity to build practical exposure to enterprise AI solutions and emerging technologies.

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