Senior Solutions Architect, Generative AI Specialist

🕒 Abril 7

🏄 California, North Carolina, +3 estados a mais – Remoto

🏄 California – Remote 🌲 North Carolina – Remote 🌲 Oregon – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $184.000 - $287.500 / ano

⏰ Tempo Integral

🟠 Sênior

💻 Engenheiro de Soluções

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

Candidatar-se

Encontrar Vagas Remotas Similares

Receber Emails de Vagas Remotas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

NVIDIA

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1993

🤖 Inteligência Artificial

🎮 Jogos

Artificial Intelligence • Gaming • Automotive

A NVIDIA é uma empresa de tecnologia líder, especializada em computação acelerada e inteligência artificial. A companhia é pioneira em avanços em unidades de processamento gráfico (GPUs), computação em nuvem, data centers e realidade virtual, com foco nos setores de games, automotivo, saúde e robótica. As inovações da empresa, como o NVIDIA Omniverse, transformam processos digitais tradicionais ao viabilizar simulações de alta fidelidade e tarefas de renderização. Suas aplicações abrangem diversos setores, desde veículos autônomos com o NVIDIA DRIVE até soluções de saúde com o NVIDIA Clara, além de análises e fluxos de trabalho impulsionados por IA.

Descrição

• Function as the chief technical representative for advanced AI partners, handling detailed technical interactions and synchronizing their roadmaps with NVIDIA's platform and emerging technology • Lead end-to-end prototyping engagements by defining requirements and crafting reference architectures that guide partners from initial concept to production-ready handoffs • Architect and build enterprise-grade agentic AI systems, RAG pipelines, and multi-modal workflows, ensuring high-performance, GPU-accelerated inference at scale • Diagnose and resolve intricate system issues and performance bottlenecks across the full AI stack, from initial model selection to large-scale deployment • Produce reusable technical assets, including implementation guides and benchmarks, that accelerate time-to-value for both partners and their customers • Collaborate with NVIDIA’s internal engineering, research, and product teams to resolve critical partner issues and speed up shared success • Champion team guidelines for technical reviews and discovery, while mentoring new members and participating in hiring panels to expand the team’s depth • Commit to continuous professional growth through formal AI/ML certifications and special projects that elevate your value within the NVIDIA ecosystem

🎯 Requisitos

• 8+ years of relevant engineering experience crafting, developing, and deploying AI/ML systems and complex LLM-powered workflows • Strong proficiency in advanced GenAI and LLM approaches, including proprietary vs. open model selection, retrieval-augmented generation (RAG), prompt engineering, and production inference optimization • Familiarity with agentic AI standards (LangGraph, LangChain, MCP) and expertise in multimodal AI systems including vision-language models and audio/video workflows • Hands-on experience with fine-tuning (PEFT, LoRA), synthetic data generation, and implementing automated AI evaluation frameworks to measure quality and safety • Strong command of GPU-optimized infrastructure (Docker, Kubernetes), microservices, and MLOps pipelines for automated training and distributed inference • Experience with AI observability (trace logging, latency monitoring) and a solid understanding of responsible AI, including guardrails, data governance, and regulatory considerations (HIPAA, GDPR) • Experience connecting cloud and on-premises deployments, hybrid architectures, and familiarity with Physical AI concepts such as simulation environments and edge inference • Proven ability to communicate complex technical concepts to diverse audiences and experience in technical engagement roles involving discovery and requirements gathering • MS or advanced degree in Computer Science, AI, or a related field—or equivalent experience.

🏖️ Benefícios

• equity • benefits