Nvidia Solutions Architect Generative AI Agents Data Processing 

United States, California 

879687718

you will be doing:

• Building agentic LLM applications and exploring the latest advancements in model training, fine-tuning and customization.

• Enabling NVIDIA strategic service delivery partners to build enterprise AI solutions using accelerated computing stack including NIMs and NeMo microserviecs.

• Collaborate with developers and onboard them to NVIDIA AI platforms and services by providing deep technical guidance.

• Anticipate customer and partners needs and find enablement opportunities to expand adoption and utilization of NVIDIA Generative AI products and platforms.

• Establishing and building repeatable reference architecture, communicate standard processes and understand solution trade-offs. Share findings and feedback to improve products and services.

ee:

• MSc, PhD in Computer Science, Electrical Engineering, Software Engineer, ML Engineer, or related fields (or equivalent experience).

• 5+ years of relevant work experience in developing and deploying AI models at scale as a Software Engineer or deep learning engineer.

• Proven track record of building enterprise-grade RAG based systems using open-source models and orchestration frameworks with strong foundation in deep learning, with a particular emphasis on generative models.

• Proficiency in Python, C++ programming and Deep Learning frameworks,

• Excellent communication and presentation skills to effectively collaborate with both internal and external customers.

Ways to stand out from thecrowd:

• Demonstrate expertise and hands-on experience with NVIDIA AI platforms. Some products of interest include natural language processing and Large Language Models (NVIDIA NeMo) and inference at scale (NIMs).

• Excellent practical knowledge of Generative AI and LLM development. Ability to train GPT and Megatron Models.

• Understanding of MLOps life cycle management and experience with LLMOps workflows.

• Experience with CUDA programming and benchmarking and analyzing performance AI Agentic systems.