L&T Off Campus Drive 2026 – Multiple Roles | Apply Online

Eligibility:

• Freshers with strong academic grounding in AI/ML are highly encouraged
• Experienced engineers (2+ years) in AI/ML roles are welcome
• Must come from Computer Science or AI/ML specialization

Note:  This role is ideal for freshers with strong AI fundamentals or engineers with up to 2+ years experience in AI/ML, data science, or Azure AI services.

Technical Skills Required:

AI/ML Fundamentals (Mandatory)

• Strong understanding of ML algorithms, deep learning, transformers, CNNs, RNNs.
• Experience with Python, PyTorch/TensorFlow.
• Knowledge of prompt engineering, embeddings, LLM behavior.

Azure Ecosystem Skills

• Azure OpenAI / Azure AI Foundry
• Azure Cognitive Services (Vision, Document Intelligence, Search)
• Azure ML, Azure Functions, Logic Apps
• Azure Blob Storage, Azure Databricks (added advantage)

Computer Vision Skills

• YOLOv8, Detectron2, OpenCV
• OCR engines – Azure OCR / Form Recognizer
• Video processing with Python/FFmpeg

NLP & Document AI

• LLM fine-tuning
• RAG (Retrieval Augmented Generation)
• Metadata extraction and reconciliation
• Clause extraction, compliance validation (added advantage)

Software Skills

• Python is mandatory
• Good understanding of DevOps, APIs and integration workflows
• Basic knowledge of SQL/NoSQL

Soft Skills

• Problem-solving mindset with strong analytical thinking
• Ability to understand complex engineering workflows
• Good communication and documentation skills
• Ability to work with cross-functional engineering teams

Key Responsibilities:

1. Azure AI & Chatbot Development

• Build AI-powered chatbots using Azure OpenAI, Azure Bot Service, Prompt Flow, and Cognitive Search.
• Develop conversational workflows for engineering, operations, and project management teams.
• Integrate chatbots with Teams, SharePoint, Azure Logic Apps, and engineering data for internal use cases.
• Fine-tune LLMs (GPT?4/40, Phi?3, etc.) using domain-specific datasets for engineering and EPC tasks.

2. Video Analytics for Safety & Operational Monitoring

• Develop and deploy deep learning–based video analytics models for:
  • PPE detection
  • Safety violations
  • Site hazard identification
  • Activity tracking
• Implement vision models (YOLOv8/Detectron2) for object detection, tracking, and anomaly detection.
• Integrate video pipelines into the Azure ecosystem (Blob → Functions → AI Models → Dashboards).

3. AI/ML for P&ID Processing & MTO Extraction

• Build systems for automatic extraction of MTO (Material Take-Off)from P&IDs using:
  • Computer vision
  • OCR (Azure Document Intelligence / Form Recognizer)
  • Graph-based engineering entity mapping
  • NLP & LLM-based reasoning for engineering validation
• Contribute to AI agent workflows for cross-verifying P&IDs, 3D models, line lists, and engineering documents.
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4. Engineering Document Automation (EPC Use Cases)

• Build models for drawing analysis, tolerance checks, metadata reconciliation, and compliance validation.
• Work with Azure AI Foundry to fine-tune models for Engineering Drawing Audit Automation.
• Support development of autonomous/agentic AI systems for EPC workflows.

About the Role:

• L&T Energy Offshore is accelerating its digital transformation by deploying advanced AI/ML solutions across Engineering, Procurement, Construction, Safety, and Compliance. We are looking for an enthusiastic AI/ML Engineer who can build, deploy, and optimize intelligent systems such as chatbots, video analytics pipelines, and engineering document automation tools (including MTO extraction from P&IDs).