1 month ago
Gurgaon, IndiaSenior
Responsibilities
- Architect end-to-end generative AI solutions focused on LLMs, agentic AI, and RAG workflows.
- Collaborate with customers to understand business requirements and design tailored technical solutions.
- Support pre-sales activities through technical presentations, demonstrations, workshops, and design sessions.
- Train, fine-tune, deploy, and optimize LLMs for production inference using NVIDIA hardware and software platforms.
- Design and integrate RAG workflows into customer applications and systems.
- Provide technical guidance on LLM training, inference optimization, GPU cluster architecture, and RAG implementation.
- Collaborate with NVIDIA engineering teams and provide feedback on generative AI technologies.
- Work with government, research, and public sector departments.
Requirements
- B.Tech, master's, or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
- 10+ years of hands-on technical experience focused on generative AI and training LLMs.
- Proven experience deploying and optimizing LLMs for production inference.
- In-depth knowledge of language models such as GPT-3 and BERT or similar architectures.
- Expertise training and fine-tuning LLMs with TensorFlow, PyTorch, or Hugging Face Transformers.
- Experience with model deployment and inference optimization on GPU-focused hardware platforms.
- Strong knowledge of GPU cluster architecture, parallel processing, and distributed computing.
- Excellent communication and collaboration skills with technical and non-technical stakeholders.
- Experience leading workshops, training sessions, and technical presentations.
- Familiarity with Docker and Kubernetes for scalable model deployment.
- Hands-on experience with NVIDIA GPU technologies and GPU cluster management.
Benefits
- Competitive salary and generous benefits package.
- Equal opportunity employer committed to a diverse work environment.
Tech Stack
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.