NVIDIA DLI Certified Trainer - Gen AI

NVIDIA DLI Certified Trainer — Agentic AI & Generative AI (LLMs)

About Dayananda Sagar University & the AI First Team
Dayananda Sagar University (DSU), Bengaluru, is home to one of India's most powerful academic AI infrastructure deployments — 20 NVIDIA DGX B200 systems, 160 GPUs, and 1.4 PetaFLOP of FP8 compute, housed within the NVIDIA AI Centre of Excellence on campus.
Under the direct mandate of our Pro-Chancellor Dr. Prem Chandra Sagar, DSU has launched the AI First Initiative — a mission-critical programme to certify 20,000 students annually through NVIDIA's Deep Learning Institute (DLI), reskill 150 faculty members, and incubate 50 Moonshot AI Projects. The AI First Team is a dedicated unit operating from the Pro-Vice Chancellor's Office, exclusively chartered for this mission.
This appointment is part of that team. It is not a conventional academic role — it is a high-impact, technology-forward position at the heart of India's academic AI transformation.

Role Overview
The NVIDIA DLI Certified Trainer will design, deliver, and continuously improve NVIDIA Deep Learning Institute certified programmes in Generative AI, Large Language Models (LLMs), and Agentic AI — using DSU's DGX B200 GPU infrastructure. The trainer will work with students, faculty, and external corporate clients, and will be a key contributor to the Train-the-Trainer programme targeting 150 DSU faculty.
This is a hands-on, delivery-intensive role requiring deep technical expertise in NVIDIA frameworks, strong communication skills, and the ability to simplify complex GPU-accelerated AI concepts for audiences ranging from beginners to PhD researchers.

Key Responsibilities & Deliverables
3.1 NVIDIA DLI Programme Delivery
Deliver official NVIDIA DLI workshops and certification programmes in Generative AI, LLMs, and Agentic AI to B.Tech students (Sem 4 & Sem 6), faculty, and research teams
Conduct hands-on labs using NVIDIA frameworks — NeMo, TensorRT-LLM, RAPIDS, Triton Inference Server, and CUDA-based pipelines — on DGX B200 JupyterHub
Manage end-to-end session logistics: environment setup, student grouping, lab execution, assessment, and certification submission to NVIDIA DLI portal
Achieve a batch completion rate of >85% and an average certification score of >75%

3.2 Agentic AI & LLM Specialisation
Guide learners through end-to-end agentic AI workflows — tool use, RAG pipelines, multi-agent orchestration, and LLM fine-tuning
Develop and maintain lab environments tailored to academic and research use cases on GPU-accelerated infrastructure
Support student Moonshot Projects involving NeMo fine-tuning, RAG-based applications, and autonomous agent systems
Stay current with NVIDIA's evolving framework releases and incorporate updates into curriculum within 30 days of release

3.3 Train-the-Trainer Programme
Co-facilitate the Train-the-Trainer programme targeting 150 DSU faculty across all Schools
Deliver intensive 3-day residential DLI bootcamps for faculty batches (30 faculty per batch)
Certify faculty at NVIDIA DLI Associate and Professional levels; maintain trainer certification dashboard
Mentor DLI School Ambassadors embedded across Schools of Engineering, ECE, Mechanical, and Management

3.4 Bootcamps, Hackathons & AI Events
Design and execute 6+ AI Bootcamps per year (3-day format; school-specific themes)
Co-lead 4+ AI Hackathons per year — including 24–48 hour events on DGX B200 infrastructure
Support 'AI First Week' campus events each semester — demonstrations, guest talks, project exhibitions
Coordinate with external NVIDIA India speakers and partner organisations for campus AI events

3.5 Corporate Training & ODL (Phase 2)
Deliver AI training programmes for corporate clients (2–5 day structured bootcamps) via DSU's ODL platform
Support the development of online PG programmes incorporating NVIDIA DLI curriculum as core credit content
Assist in proposal preparation and delivery planning for B2B corporate training engagements

3.6 Curriculum & Quality
Collaborate with the DLI Curriculum Lead and Pro-Vice Chancellor's Office on curriculum design and NVIDIA DLI compliance
Maintain lab documentation, session recordings, and student progress logs for each cohort
Participate in monthly KPI reviews and provide data for Pro-Chancellor reporting

Qualifications & Requirements
Mandatory Requirements
Active NVIDIA DLI Certified Instructor status — or demonstrated eligibility and commitment to certify within 60 days of joining
Deep hands-on expertise in CUDA architecture — kernel programming, memory hierarchy, thread block models, and parallelism
Practical experience building and deploying LLM-based applications — fine-tuning (LoRA / QLoRA), RAG systems, prompt engineering, and agent frameworks (LangChain, LlamaIndex, AutoGen, or similar)
Proficiency with NVIDIA's AI stack: NeMo Toolkit, TensorRT-LLM, Triton Inference Server, RAPIDS, cuDNN, cuBLAS
Strong Python programming skills; hands-on experience with PyTorch and/or JAX in GPU-accelerated environments
Experience with Agentic AI systems — planning loops, tool-calling, memory modules, and multi-step reasoning pipelines
Ability to deliver technically rigorous content to mixed audiences — from first-year undergraduates to PhD researchers

Educational Qualification
B.Tech / M.Tech / M.S. / PhD in Computer Science, Artificial Intelligence, Electronics, Data Science, or a closely related field
Minimum 3 years of hands-on industry or research experience in AI/ML with GPU computing
NVIDIA DLI Instructor Certification: active or verifiably in progress

DATE: 10-05-2026
DR. D. PREMACHANDRA SAGAR
PRO CHANCELLOR, DSU