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Nvidia Solutions Architect Generative AI United States, Texas 68482514
01.12.2024
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What you’ll be doing
- Develop and demonstrate software solutions based on NVIDIA’s ground breaking AI software and hardware technologies to customers. Develop GenAI model pipeline and perform in-depth analysis and optimization to ensure the best performance on current- and next-generation GPU architectures
- Develop and debug software for NVIDIA and OSS AI frameworks and libraries
- Lead and develop proof-of-concepts (PoCs) for software solutions applied to Consumer Internet industry use-cases such as NLP/LLM, retrieval, recommender, etc. by working closely with customer's AI developers. Build collateral (notebook/code) for PoCs
- Work closely with business development team owning the technical relationship and enabling customer in building innovative solutions based on NVIDIA technologies
- Partner with NVIDIA software engineering, product, sales teams to secure design wins at customers. Enable development and growth of NVIDIA product features through customer feedback and PoC evaluations
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields or equivalent experience
- 5+ years of experience as an AI/Software Engineer with proven track record coding in Python and/or C++ with popular AI software libraries and GPUs
- Experience with GenAI applications and LLMtraining/fine-tuning,inference optimization and/or RAG pipelines
- Ability to communicate your ideas/code clearly through GitHub, documentation
- Great teammate who enjoys collaborating with teams across the organization such asEngineering/Research,Sales, Product, and Marketing
- Effective verbal/written communication, and technical presentation skills
- Self-starter with passion for growth, enthusiasm for continuous learning and sharing findings across the team
- Experience working with enterprise developers and customer facing skills
- Experience with large-scale production data pipelines and AI model training/deployment
- Knowledge of MLOps technologies such as containers, Kubernetes, data center deployments etc.
- Able to think creatively to debug and solve complex problems
You will also be eligible for equity and .
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