L&T Energy Hydrocarbon is excited to announce its Off Campus Drive 2026, a significant recruitment initiative targeting bright minds for the role of Junior AI/ML Engineer. This drive is specifically hosted at their Powai campus and is open to candidates with 0-2 years of experience in the field. This strategic recruitment effort underscores L&T’s commitment to bolstering its technical workforce and driving innovation within the dynamic hydrocarbon sector.
L&T Energy Off Campus Drive Overview:-
| Job Title | AI/ML Engineer |
| Qualification | BE/B.Tech/BCA/MCA/ME/M.Tech or Related |
| Batch | Any |
| Experience | Freshers-2 Year+ |
| Salary | Best in Industry |
| Job Location | Powai |
| Drive Location | Online |
| Drive Date | Announced Later |
| Last Date | ASAP |
Job Description ::
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).
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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.
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.
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
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
How to Apply :-
The interested and eligible graduates register on the following apply link as soon as possible.
Apply Link For L&T Off Campus : Click Here
