Larsen & Toubro Urgent Recruitment 2026 – GenAI Trainee || Powai : Are you looking for exciting Machine Learning Jobs, Artificial Intelligence Jobs, Generative AI Jobs, or Computer Vision Jobs? This opportunity is ideal for candidates with a strong academic background in technology and an interest in developing next-generation AI solutions.
Machine Learning, AI & Computer Vision Jobs: Skills, Qualifications, Roles and Responsibilities
The role focuses on Machine Learning, Artificial Intelligence, Generative AI, Computer Vision, Data Analytics, and AI Solution Development. Candidates will get an opportunity to work on real-world AI applications, machine learning models, large language models (LLMs), computer vision systems, data pipelines, and intelligent automation solutions.
Required Experience :- 0 – 2 years
End Date :- 09 Feb 2027
GenAI Trainee : Job Overview
| Category | Details |
|---|---|
| Job Domain | Machine Learning, Artificial Intelligence, Generative AI & Computer Vision |
| Key Skills | Machine Learning, Computer Vision, Artificial Intelligence |
| Minimum Qualification | BTech & MTech |
| Work Areas | AI/ML, Generative AI, Computer Vision, Data Analytics & AI Engineering |
Skills Required
Candidates interested in this opportunity should have an interest or foundational knowledge in:
- Machine Learning
- Artificial Intelligence
- Computer Vision
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Data Analytics
- AI model development
- Data preprocessing and analysis
- AI application development
Knowledge of popular AI and machine learning frameworks and tools can also be beneficial, particularly OpenCV, TensorFlow, PyTorch, and YOLO.
Minimum Educational Qualification
The minimum qualification for this opportunity of Larsen & Toubro Urgent Recruitment 2026 – GenAI Trainee is:
- Bachelor of Technology (BTech)
- Master of Technology (MTech)
Candidates from relevant technology and engineering backgrounds who are interested in AI, Machine Learning, Deep Learning, or Computer Vision can consider this opportunity.
Roles and Responsibilities
1. Machine Learning & Artificial Intelligence
The selected candidates will support the development and implementation of machine learning and artificial intelligence solutions.
Key responsibilities include:
- 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, model tuning, and performance optimization.
- Conducting model validation, testing, benchmarking, and documentation.
- Supporting the deployment and monitoring of AI/ML models in development and production environments.
- Analyzing model performance and recommending improvements in accuracy and efficiency.
This role provides an opportunity to gain practical exposure to the complete machine learning lifecycle, from data preparation and model development to deployment and monitoring.
2. Generative AI Development
Generative AI is rapidly becoming an important area of technology, and this role involves working with modern AI technologies including Large Language Models (LLMs) and multimodal AI models.
Responsibilities include:
- Supporting the development of applications using Large Language Models and multimodal AI models.
- Working on prompt engineering, prompt optimization, and response evaluation.
- Participating in Retrieval-Augmented Generation (RAG), fine-tuning, and model customization projects.
- Developing and testing AI-powered chatbots and virtual assistants.
- Supporting content generation solutions powered by Generative AI.
- Evaluating AI model outputs for quality, factual accuracy, safety, and compliance with Responsible AI practices.
- Integrating Generative AI capabilities into enterprise applications using APIs and frameworks.
Candidates interested in Generative AI careers and LLM-based applications can gain valuable exposure through these responsibilities.
3. Computer Vision Engineering
Computer Vision is another major area covered by this opportunity. Candidates will support the development of image and video analytics solutions using modern computer vision techniques.
Responsibilities include:
- Supporting the development of image and video analytics solutions.
- Working with object detection, image classification, segmentation, tracking, and OCR models.
- Managing image and video datasets for annotation, labeling, augmentation, and preprocessing.
- Supporting deep learning model development using frameworks such as OpenCV, TensorFlow, PyTorch, and YOLO.
- Assisting with the deployment and optimization of computer vision models for edge devices, cloud platforms, and real-time applications.
- Performing quality assessments and accuracy analysis of computer vision systems.
This makes the opportunity particularly relevant for candidates interested in Computer Vision Engineer Jobs, AI Vision Jobs, and Deep Learning Jobs.
4. Data Analytics & Engineering
Data plays an important role in building successful AI systems. Candidates will also contribute to data analysis and engineering activities.
Responsibilities include:
- Conducting Exploratory Data Analysis (EDA).
- Generating insights from large datasets.
- Creating visualizations, reports, and dashboards.
- Supporting the development of data pipelines and workflows for AI applications.
- Maintaining data quality, integrity, and governance standards.
- Managing and processing image, text, audio, and video datasets.
Candidates can therefore develop experience across both AI engineering and data analytics workflows.
5. AI Solution Development & Integration
The role also involves supporting the development of intelligent business solutions and integrating AI technologies into applications.
Key responsibilities include:
- Collaborating on AI-driven business solutions and intelligent automation projects.
- Integrating AI, Generative AI, and Computer Vision models with web, mobile, and enterprise applications.
- Supporting the development of APIs, microservices, and cloud-based AI solutions.
- Participating in software testing, debugging, and troubleshooting.
- Following coding standards, version control, and software development best practices.
This experience can help candidates understand how AI models are transformed into practical, production-ready applications.
6. Research & Innovation
AI is an evolving field, so continuous learning and experimentation are important parts of the role.
Candidates may be expected to:
- Stay updated with developments in Artificial Intelligence, Machine Learning, Generative AI, Computer Vision, and Deep Learning.
- Develop Proof-of-Concept (PoC) solutions for emerging technologies and use cases.
- Evaluate new AI frameworks, tools, and platforms.
- Contribute innovative ideas to improve AI products, services, and operational processes.
- Participate in technical discussions, hackathons, and innovation initiatives.
7. Documentation & Compliance
Responsible development and proper documentation are essential when working with AI systems.
Responsibilities include:
- Preparing technical documentation, model documentation, and project reports.
- Documenting datasets, training procedures, model evaluations, and deployment processes.
- Following Responsible AI, cybersecurity, data privacy, and ethical AI guidelines.
- Ensuring compliance with organizational, industry, and regulatory standards.
8. Collaboration & Continuous Learning
AI development requires collaboration between multiple technical and business teams.
Candidates will work closely with:
- AI Engineers
- Data Scientists
- Software Developers
- Product Teams
- Business Stakeholders
The role may also involve participating in Agile ceremonies, code reviews, technical meetings, mentoring, and training programs.
Continuous self-learning and willingness to adopt emerging technologies will be important for success in this position.
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Why This AI/ML Opportunity Is Important for Job Seekers
Larsen & Toubro Urgent Recruitment 2026 – GenAI Trainee : The demand for professionals with knowledge of Artificial Intelligence, Machine Learning, Generative AI, Deep Learning, and Computer Vision continues to grow as organizations adopt AI-powered applications and automation.
This opportunity covers several important areas of the modern AI ecosystem, including:
- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models
- Retrieval-Augmented Generation
- Computer Vision
- OCR
- Data Analytics
- AI APIs
- Cloud-based AI solutions
- Intelligent automation
- Responsible AI
For BTech and MTech graduates interested in building a career in artificial intelligence, these areas can provide a strong foundation for long-term growth.
Who Can Apply?
This opportunity can be suitable for candidates who:
- Hold a BTech or MTech qualification.
- Are interested in Machine Learning and Artificial Intelligence.
- Want to build a career in Generative AI or Computer Vision.
- Have an interest in developing AI-powered applications.
- Enjoy working with datasets and AI models.
- Want to learn modern AI frameworks and technologies.
- Are willing to continuously learn emerging technologies.
How to Apply for Larsen & Toubro Urgent Recruitment 2026 – GenAI Trainee : L&T Jobs
Interested candidates for L&T Recruitment can apply through the official L&T Careers page using the link below.
| L&T Apply Link | Click HERE |
| Join Telegram (Must) | Click Here |
| Join Experienced Job Telegram | Click Here |
| Follow Instagram Job Page Link: | Join Here |
Career Areas Related to This Opportunity
Candidates gaining experience in these areas can explore career paths such as:
- Machine Learning Engineer
- Artificial Intelligence Engineer
- Generative AI Engineer
- Computer Vision Engineer
- Deep Learning Engineer
- AI Software Engineer
- Data Scientist
- AI/ML Developer
- Computer Vision Developer
- AI Research Engineer
Final Takeaway – Larsen & Toubro Urgent Recruitment 2026 – GenAI Trainee :
This opportunity is well suited for BTech and MTech graduates interested in Machine Learning, Artificial Intelligence, Generative AI, Computer Vision, and Deep Learning.
With responsibilities spanning AI model development, LLM applications, RAG, computer vision, data analytics, AI integration, research, and Responsible AI, the role offers exposure to multiple areas of the rapidly evolving AI ecosystem.
Candidates looking to start or strengthen their careers in Machine Learning and Artificial Intelligence should consider developing practical skills in machine learning algorithms, deep learning, Python-based AI development, computer vision, Generative AI, LLMs, data analysis, and model deployment.
