Data Scientist

Overview

• Job Title & Summary
  
  

Agentic AI)

Drive cutting-edge research and development in autonomous AI agents, Agentic AI, and GenAI systems to power next-gen airline solutions.

• Key Responsibilities
• Design, develop, and deploy autonomous AI agents using Agentic AI frameworks.
• Build and optimize multi-agent collaboration protocols (MCP, A2A) for scalable decision-making systems.
• Fine-tune large language models (LLMs) for domain-specific airline use cases.
• Architect and implement GenAI solutions for operational and customer-facing applications.
• Conduct experiments and benchmarking for model performance and reliability.
• Collaborate with engineering teams to integrate AI models into cloud-native environments (Azure/GCP).
• Publish findings, contribute to patents, and represent the lab in external forums and conferences.
• Required Skills / Must-Have
• Technical Skills: Python, PyTorch/TensorFlow, LangChain, FastAPI, Azure ML or Vertex AI, Docker/Kubernetes.
• AI/ML Expertise: Autonomous agents, Agentic AI, LLM fine-tuning, GenAI pipelines.
• Protocols: MCP (Multi-agent Collaboration Protocol), A2A (Agent-to-Agent Communication).
• Cloud Platforms: Azure or GCP (hands-on experience).
• Experience: 4–7 years in applied AI/ML, preferably in innovation or R&D settings.
• Nice-to-Have / Preferred Skills
• Experience with airline industry datasets or operational systems.
• Familiarity with Reinforcement Learning (RL) and multi-agent systems.
• Knowledge of MLOps practices and CI/CD for ML workflows.
• Contributions to open-source AI projects or publications in top-tier conferences.
• Education & Qualifications
• Primary: Master’s or PhD in Computer Science, AI/ML, Data Science, or related field.
• Secondary: Bachelor’s in Engineering or Mathematics with strong AI/ML experience.
• Certifications/Licenses
• Preferred: Azure AI Engineer Associate, Google Cloud ML Engineer, TensorFlow Developer Certificate.
• Skills Grouping & Synonyms
• AI/ML: “Autonomous agents / Agentic AI / multi-agent systems / GenAI / LLM fine-tuning”
• Cloud: “Azure ML / GCP Vertex AI / cloud-native ML / MLOps”
• Protocols: “MCP / multi-agent collaboration / A2A / agent communication”
• Development: “Python / FastAPI / LangChain / PyTorch / TensorFlow”
• Location & Work Mode
  
  

Gurgaon – Work from office