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Senior Solutions Architect, Gen AI

🕒 July 28

🏄 California – Remote

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💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

🦅 H1B Visa Sponsor

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👻 Ghost score 26%

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Provide hands-on technical mentorship to partners and customers on NVIDIA's GenAI stack • Guide customers in developing and deploying Agentic AI workflows on NVIDIA platforms • Quantify benefits of accelerated computing software and hardware • Build demonstrations and proofs of concept addressing customers' critical business needs • Help draft requirements for missing features to unblock customer and partner progress • Educate customers on new NVIDIA GenAI technologies and platforms • Prepare and deliver technical training presentations and workshops • Build industry-use-case collateral, including notebooks and blogs • Partner with NVIDIA engineering, product, and sales teams to secure customer design wins • Enable development and growth of NVIDIA product features through customer feedback and POC evaluations

🎯 Requirements

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience • 8+ years of hands-on experience in a technical AI role, with a strong emphasis on Gen AI • Proficient in the latest model architectures and able to articulate their computational complexities • Proven track record deploying and optimizing LLM models for production inference using vLLM, TRT-LLM, SGLang, or similar inferencing engines • Expertise training and fine-tuning LLMs using TensorFlow, PyTorch, or Hugging Face Transformers • Solid understanding of GPU cluster architecture and parallel processing for accelerated model training and inference • Experience with Docker, Kubernetes, GitLab, Linux Command Line, Shell, and similar DevOps tools • Excellent communication and teamwork skills, with ability to explain complex technical concepts to technical and non-technical collaborators • Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences • Experience with Agentic AI frameworks, tools, and protocols such as LangChain, LangGraph, and MCP • Understanding of Multimodal LLMs and VLMs • Experience deploying LLM models at scale on AWS, Azure, or GCP • Proven track record profiling and optimizing inference latency, throughput, memory, and I/O utilization • Mathematical understanding of parallelisation techniques in Gen AI

🏖️ Benefits

• Equity • Benefits

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