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Larsen & Toubro (L&T) has announced a new opportunity for the position of GenAI Trainee for candidates interested in Artificial Intelligence, Generative AI, Machine Learning, Deep Learning, Computer Vision, and Data Analytics. The position is available under DEIC – L&T Precision Engineering & Systems IC at the L&T Innovation Campus, Powai.
This opportunity is suitable for candidates with 0 to 2 years of experience and requires a Bachelor of Technology (B.Tech) or Master of Technology (M.Tech) qualification. Fresh graduates and early career professionals who have a strong interest in artificial intelligence and emerging technologies can consider this opportunity.
The job reference number for this position is LNT/GT/1820286. According to the job listing, the position was posted on 13 August 2026, and the application end date is 9 February 2027.
The GenAI Trainee role is particularly relevant for candidates who want to build their careers around modern AI technologies. The position covers Generative AI, Large Language Models, Retrieval-Augmented Generation, prompt engineering, Machine Learning, Computer Vision, Deep Learning, Data Analytics, AI APIs, microservices, cloud-based AI solutions, and AI research and innovation.
L&T GenAI Trainee Recruitment 2026 – Overview
The position offered by L&T is GenAI Trainee and the job reference is LNT/GT/1820286. The role is part of DEIC – L&T Precision Engineering & Systems IC and is located at the L&T Innovation Campus, Powai.
Candidates with 0 to 2 years of experience can apply for the opportunity. The minimum educational qualification mentioned in the job listing is Bachelor of Technology (B.Tech) or Master of Technology (M.Tech).
The primary technical areas associated with this role are Machine Learning, Computer Vision, and Artificial Intelligence.
The position was posted on 13 August 2026, while the listed application end date is 9 February 2027.
About L&T
Larsen & Toubro is one of India's major engineering and technology organizations, operating across several industries and business segments. The company works across engineering, manufacturing, technology, construction, infrastructure, and other specialized areas.
L&T continues to invest in advanced engineering and technology capabilities, including Artificial Intelligence, Machine Learning, automation, digital technologies, and intelligent systems.
The L&T Precision Engineering & Systems business is focused on advanced engineering and precision technology solutions. The GenAI Trainee position provides an opportunity for candidates to work in an environment where AI and emerging technologies can be applied to practical engineering and enterprise use cases.
For graduates who want to develop their technical careers in Artificial Intelligence and Generative AI, this position can provide valuable exposure to real-world projects and modern AI development practices.
L&T GenAI Trainee Job Description
The GenAI Trainee will support projects across multiple areas of Artificial Intelligence and Machine Learning. The responsibilities cover the complete AI development lifecycle, including data preparation, model development, evaluation, deployment, optimization, application integration, research, documentation, and collaboration.
The role is not limited to Generative AI alone. Candidates can gain exposure to Machine Learning, Deep Learning, Computer Vision, Data Analytics, AI application development, Large Language Models, multimodal AI, Retrieval-Augmented Generation, and AI-powered enterprise solutions.
Since the position is a trainee-level role, candidates will also be expected to learn continuously and work closely with experienced AI Engineers, Data Scientists, Software Developers, Product Teams, and Business Stakeholders.
Machine Learning and Artificial Intelligence
The role involves supporting different stages of Machine Learning and Artificial Intelligence development. Candidates may assist with collecting, cleansing, preprocessing, and validating structured and unstructured datasets.
Trainees may also support the design, development, training, and evaluation of Machine Learning and Deep Learning models. This can provide practical exposure to the process of converting raw data into useful machine learning solutions.
Feature engineering, model tuning, and performance optimization are also included in the responsibilities. Candidates may work on improving model performance and identifying ways to increase accuracy and efficiency.
The role also involves model validation, testing, benchmarking, and documentation. Candidates may assist with deploying and monitoring AI and Machine Learning models in both development and production environments.
Another important responsibility is analyzing model performance and recommending improvements where necessary.
Generative AI Development
Generative AI is one of the major areas covered by this L&T opportunity. Candidates will assist in developing applications that use Large Language Models and multimodal AI models.
The role includes exposure to prompt engineering, prompt optimization, and response evaluation. Candidates may learn how to design and improve prompts and evaluate the quality of AI-generated responses.
The position also specifically mentions Retrieval-Augmented Generation, fine-tuning, and model customization. This means candidates can gain exposure to modern techniques used for developing enterprise-focused Generative AI applications.
Trainees may also work on AI-powered chatbots, virtual assistants, and content generation solutions.
Evaluating model outputs is another important part of the role. Candidates may need to assess AI responses for quality, factual accuracy, safety, and compliance with Responsible AI practices.
The role also involves integrating Generative AI capabilities into enterprise applications using APIs and suitable AI frameworks.
Large Language Models and RAG
Candidates interested in Large Language Models can gain practical exposure through this position. LLMs are increasingly being used for enterprise chatbots, virtual assistants, document processing, knowledge systems, content generation, and intelligent automation.
The job description specifically mentions Retrieval-Augmented Generation, commonly known as RAG. RAG allows an AI application to retrieve relevant information from external sources before generating a response.
Candidates may participate in RAG projects and learn how AI applications can work with enterprise-specific information and knowledge bases.
Knowledge of LLM APIs, vector databases, embeddings, prompt engineering, and basic RAG architecture can be useful for candidates who want to prepare for this role.
Computer Vision Engineering
Computer Vision is another major technical area included in the GenAI Trainee position.
Candidates may assist in developing image and video analytics solutions using Computer Vision techniques. The responsibilities include working with technologies related to object detection, image classification, image segmentation, object tracking, and Optical Character Recognition.
The role also involves working with image and video datasets. Candidates may participate in dataset annotation, labeling, augmentation, and preprocessing activities.
Trainees can gain exposure to the development and evaluation of Deep Learning models for computer vision applications.
Computer Vision Frameworks
The job description specifically mentions OpenCV, TensorFlow, PyTorch, and YOLO.
OpenCV is widely used for image processing and computer vision applications, while TensorFlow and PyTorch are popular frameworks for developing and training Machine Learning and Deep Learning models.
YOLO is commonly used for real-time object detection applications.
Candidates who have completed projects involving these frameworks can highlight them on their resumes. Practical experience with object detection, image classification, OCR, image segmentation, or video analytics can be particularly relevant.
The role may also involve deploying and optimizing Computer Vision models for edge devices, cloud platforms, and real-time applications.
Data Analytics and Engineering
The GenAI Trainee position also includes responsibilities related to Data Analytics and Data Engineering.
Candidates may conduct Exploratory Data Analysis, commonly known as EDA, to understand datasets and identify meaningful patterns.
The role may involve creating visualizations, reports, and dashboards to communicate analytical findings effectively.
Candidates may also support the development of data pipelines and workflows required for AI applications.
Maintaining data quality, data integrity, and governance standards is another important responsibility.
The role can involve working with different types of data, including image, text, audio, and video datasets.
AI Solution Development and Integration
Candidates will also assist in building intelligent automation and AI-driven business solutions.
The role involves integrating Artificial Intelligence, Generative AI, and Computer Vision models with web applications, mobile applications, and enterprise applications.
Candidates may assist in developing APIs, microservices, and cloud-based AI solutions. This can provide useful exposure to how AI models are connected with software systems and business applications.
Software testing, debugging, and troubleshooting are also part of the responsibilities.
Candidates will be expected to follow coding standards, use version control systems, and follow software development best practices while working on AI solutions.
APIs, Microservices and Cloud AI
Modern AI applications often require integration between AI models and existing software systems. The GenAI Trainee role provides exposure to this area through API and microservice development.
Candidates may work on services that allow AI models to communicate with web applications, mobile applications, enterprise systems, or other backend components.
Knowledge of REST APIs, backend development, microservices, cloud platforms, and software architecture can therefore be useful for candidates applying for this position.
Candidates do not necessarily need to be experts in every technology mentioned, but a strong willingness to learn and experiment with modern AI development practices can be valuable.
Research and Innovation
The position also involves research and innovation activities. Candidates are expected to stay updated with developments in Artificial Intelligence, Machine Learning, Generative AI, Computer Vision, and Deep Learning.
Trainees may work on Proof of Concept development for emerging technologies and potential business use cases.
They may also evaluate new AI frameworks, tools, and platforms to determine their potential adoption.
The role encourages candidates to contribute innovative ideas that can improve AI products, services, and operational processes.
Participation in technical discussions, hackathons, and innovation initiatives may also be part of the role.
Documentation and Compliance
Documentation is an important part of professional AI development. Candidates may prepare technical documentation, model documentation, project reports, and other project-related materials.
The responsibilities include documenting datasets, training procedures, model evaluation results, and deployment processes.
The role also emphasizes Responsible AI, cybersecurity, data privacy, and ethical AI guidelines.
Candidates will need to understand that AI systems must be developed and deployed responsibly while following organizational, industry, and regulatory standards.
Collaboration and Learning
The GenAI Trainee will work closely with professionals from different technical and business teams.
The role can involve collaboration with AI Engineers, Data Scientists, Software Developers, Product Teams, and Business Stakeholders.
Candidates may participate in Agile ceremonies, code reviews, technical discussions, and regular team meetings.
Continuous learning is an important part of the position. Candidates are expected to improve their technical knowledge through training, mentoring, self-learning, and practical experience.
A proactive attitude toward learning and adopting emerging technologies will be important for candidates working in this role.
Eligibility Criteria
Candidates with 0 to 2 years of experience can consider applying for this position.
The minimum qualification mentioned in the job listing is B.Tech or M.Tech.
Candidates should have knowledge or interest in Artificial Intelligence, Machine Learning, Computer Vision, Deep Learning, Generative AI, or related technologies.
Fresh graduates who have completed relevant academic projects in AI, Machine Learning, Data Science, Computer Vision, or Generative AI can consider this opportunity.
Technical Skills
The primary skills mentioned for the position are Machine Learning, Computer Vision, and Artificial Intelligence.
Candidates can strengthen their profiles by gaining practical knowledge of Python, Machine Learning algorithms, Deep Learning, LLMs, RAG, prompt engineering, Computer Vision, APIs, and cloud technologies.
Knowledge of OpenCV, TensorFlow, PyTorch, and YOLO can also be useful, particularly for Computer Vision-related responsibilities.
Candidates who have worked on AI applications using LLM APIs or built Computer Vision projects should clearly mention those projects on their resumes.
Who Should Apply?
This opportunity can be suitable for B.Tech and M.Tech graduates who want to build careers in Artificial Intelligence and emerging technologies.
Candidates interested in Generative AI, Large Language Models, Machine Learning, Deep Learning, Computer Vision, Data Science, AI Engineering, intelligent automation, or AI application development can consider applying.
Students who have completed AI or Machine Learning projects during their academic studies can highlight those projects.
Candidates who have participated in AI hackathons, developed chatbots, experimented with LLM APIs, created RAG applications, developed object detection models, or worked on Machine Learning projects can also demonstrate relevant practical experience.
AI Projects That Can Strengthen Your Resume
Candidates applying for this role can benefit from having practical AI projects.
A candidate who has developed an LLM-powered chatbot can demonstrate knowledge of Generative AI and API integration.
A RAG-based question-answering application can demonstrate understanding of retrieval systems and LLM applications.
An object detection project using YOLO can demonstrate Computer Vision experience.
An image classification or OCR project can demonstrate knowledge of image processing and Deep Learning.
Machine Learning prediction projects can demonstrate knowledge of data preprocessing, feature engineering, model training, evaluation, and optimization.
Candidates should be prepared to explain their projects in detail during interviews, including the problem statement, dataset, preprocessing methods, model selection, evaluation metrics, challenges, and final results.
Resume Preparation Tips
Candidates should create a resume that clearly highlights their Artificial Intelligence and Machine Learning experience.
Relevant AI and GenAI projects should be placed prominently in the resume, especially if they involve LLMs, RAG, Computer Vision, Deep Learning, or AI APIs.
Candidates should explain what they actually built rather than simply listing technologies.
For example, instead of mentioning only "Python, PyTorch, YOLO," candidates can explain how they used those technologies to build and evaluate an object detection application.
Candidates should also include internships, research work, hackathons, certifications, GitHub projects, and relevant academic achievements where applicable.
L&T GenAI Trainee Recruitment 2026 – Job Details
Company: Larsen & Toubro
Job Role: GenAI Trainee
Job Reference: LNT/GT/1820286
Business Unit: DEIC – L&T Precision Engineering & Systems IC
Location: L&T Innovation Campus, Powai
Experience: 0–2 Years
Qualification: B.Tech / M.Tech
Primary Skills: Machine Learning, Computer Vision, Artificial Intelligence
Posted On: 13 August 2026
Application End Date: 9 February 2027
Frequently Asked Questions
Who can apply for the L&T GenAI Trainee position?
Candidates with 0–2 years of experience and a B.Tech or M.Tech qualification can consider applying for this position, subject to the complete eligibility requirements of the company.
What is the job role at L&T?
The position is GenAI Trainee and involves Artificial Intelligence, Generative AI, Machine Learning, Computer Vision, Deep Learning, Data Analytics, AI solution development, research, and innovation.
Where is the L&T GenAI Trainee job located?
The position is based at the L&T Innovation Campus, Powai.
What are the main skills required?
The job listing highlights Machine Learning, Computer Vision, and Artificial Intelligence as the key skills.
Does this role involve Generative AI?
Yes. The responsibilities include Large Language Models, multimodal AI, prompt engineering, RAG, fine-tuning, model customization, AI chatbots, virtual assistants, content generation, and GenAI API integration.
Does this role involve Computer Vision?
Yes. Candidates may work with object detection, image classification, segmentation, tracking, OCR, image and video analytics, and Deep Learning models.
Which Computer Vision frameworks are mentioned?
The job description mentions OpenCV, TensorFlow, PyTorch, and YOLO.
What is the experience requirement?
The required experience is 0–2 years, making the position relevant to fresh graduates and early-career professionals.
What is the minimum educational qualification?
The minimum qualification mentioned is Bachelor of Technology (B.Tech) or Master of Technology (M.Tech).
When was the job posted?
The position was posted on 13 August 2026.
What is the application deadline?
The listed application end date is 9 February 2027.
Final Words
The L&T GenAI Trainee Recruitment 2026 is an opportunity for B.Tech and M.Tech graduates who want to start or develop their careers in Artificial Intelligence, Generative AI, Machine Learning, Deep Learning, and Computer Vision.
The role provides exposure to modern AI technologies including Large Language Models, RAG, prompt engineering, fine-tuning, multimodal AI, Computer Vision, Deep Learning, AI APIs, microservices, cloud-based AI solutions, and intelligent automation.
The position also goes beyond technical development by including research, innovation, documentation, Responsible AI, data privacy, cybersecurity, collaboration, and continuous learning.
With an experience requirement of 0–2 years, the role can be particularly relevant for fresh graduates and early-career candidates who have strong interest in AI and practical project experience.
Candidates interested in this opportunity should prepare a strong AI-focused resume, highlight relevant projects and technical skills, verify the complete eligibility criteria, and apply before the listed 9 February 2027 deadline.
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