AI/ML Developer
6 days ago
Join Our Team
Were Hiring: AIML Engineer.
Job Location: Noida (Sector-63)
About Us:
Founded in 2000, Chetu is a global leader in providing tailored software development solutions and support services. Chetu's dedicated team of technology professionals offers an extensive array of software solutions, including custom application development, enterprise software integration, mobile app development, cloud computing solutions, IOT (Internet of Things) development, artificial intelligence and machine learning solutions, blockchain development, cybersecurity services, data analytics solutions, ERP (Enterprise Resource Planning) implementation, CRM (Customer Relationship Management) customization, and software testing and quality assurance. Chetu's specialized expertise caters to startups, SMBs, and Fortune 5000 companies alike, offering a flexible and scalable software delivery model tailored to each client's unique requirements. Headquartered in Sunrise, Florida, Chetu operates from 13 strategic locations across the United States and internationally.
Job summary:
Required Skillset
• Hands on experience of working with Python
• Hands on experience of working with fastapi web framework
• Comfortable with LLM(Openai,gemini or opensource), document stores (e.g., MongoDB),graph databases (Neo4j, GraphDB, or similar).
• Practical understanding of Retrieval-Augmented Generation (RAG), multimodal context fusion (VideoRAG-style), and LLM orchestration.
• Exposure to conversational systems or chatbot architecture
• Experience handling live streaming video data as well as video files.
• Experience on building agentic decision workflows and feedback-driven improvement loops using Langgraph, Crewai, Autogen or similar agentic framework.
• Values latency optimization, observability, and reliability in production AI systems.
• Deployment experience of the agentic workflows. Responsibilities
• Develop and maintain FastAPI endpoints for video ingestion, processing, and downstream pipelines.
• Support construction of VideoRAG-style contextual representations and integrate them with LLMs for summarization and analysis.
• Maintain, query, and synchronize the knowledge graph; ensure it reflects agent outputs and human feedback.
• Design and implement logic to trigger automated SOP creation and surface unclear or anomalous procedural steps.
• Contribute to a user-facing chatbot interface that fuses video, graph, and LLM context for responsive querying.
• Capture human feedback (e.g., ratings/flags) and route signals to improvement pipelines.
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