FAQs
What is the main focus of the Deep Learning Solution Architect role at NVIDIA?
The main focus of the role is to bring technical expertise about NVIDIA's advancements in LLM, MLLM, Generative AI, and RAGs to partners and customers, guiding them through the sales process and assisting in building innovative solutions based on NVIDIA technology.
What qualifications are required for this position?
A B.Tech in Engineering, Mathematics, Physics, or Computer Science is required, along with 2+ years of Deep Learning experience. An MS degree is desirable.
What specific skills are necessary for this role?
Candidates should have experience with modern Deep Learning software architecture, customer-facing skills, exposure to infrastructure management tools like SLURM and Kubernetes, and expertise in training LLMs using frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
Is hands-on experience with NVIDIA GPU technologies important for this job?
Yes, hands-on experience with NVIDIA GPU technologies and the ability to design and implement scalable workflows for LLM training and inference on GPU clusters is highly valuable.
Will there be any travel required for this job?
Yes, while extensive use of conferencing tools is made, occasional travel is required for local on-site visits to customers and data science conferences.
What soft skills are emphasized for this position?
Strong teamwork and interpersonal skills, the ability to multitask in a fast-paced environment, and strong analytical and problem-solving skills are emphasized for this role.
How does NVIDIA view diversity in the workplace?
NVIDIA is committed to fostering a diverse work environment and is proud to be an equal-opportunity employer, emphasizing that they do not discriminate based on various protected characteristics.