10 hours ago
Mumbai, IndiaSenior
Responsibilities
- Architect end-to-end generative AI solutions focused on LLMs and RAG workflows.
- Collaborate with customers to understand language-related business challenges and design tailored solutions.
- Support pre-sales activities through technical presentations and demonstrations.
- Lead workshops, design sessions, training sessions, and technical guidance for diverse audiences.
- Train, fine-tune, optimize, and deploy LLMs for efficient production inference on GPU platforms.
- Design and integrate RAG-based workflows into customer applications and systems.
- Collaborate with NVIDIA engineering teams to provide feedback and contribute to generative AI technology evolution.
- Provide technical leadership on best practices for LLM training and RAG implementation.
Requirements
- Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
- 5+ years of hands-on technical experience focused on generative AI and LLM training.
- Proven experience deploying and optimizing LLMs for production inference.
- In-depth understanding of language models including GPT-3, BERT, or similar architectures.
- Expertise training and fine-tuning LLMs with TensorFlow, PyTorch, or Hugging Face Transformers.
- Proficiency in model deployment and optimization for efficient inference on GPU hardware.
- Strong knowledge of GPU cluster architecture and parallel processing for model training and inference.
- Excellent communication and collaboration skills with technical and non-technical stakeholders.
- Experience leading workshops, training sessions, and technical presentations.
- Experience deploying LLMs in AWS, Azure, GCP, or on-premises environments is preferred.
- Experience optimizing LLM inference speed, memory efficiency, and resource utilization is preferred.
- Familiarity with Docker and Kubernetes for scalable model deployment is preferred.
- Experience with NVIDIA GPU technologies, GPU cluster management, and distributed workflows is preferred.
Benefits
- Competitive salary and generous benefits package.
- NVIDIA is committed to a diverse work environment and is an equal opportunity employer.
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.