
10,000+ employees
Founded 1993
🤖 Artificial Intelligence
🎮 Gaming
Artificial Intelligence • Gaming • Automotive
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.
🕒 April 7
🏄 California, North Carolina, +3 more states – Remote
💵 $184k - $287.5k / year
⏰ Full Time
🟠 Senior
💻 Solutions Engineer
🦅 H1B Visa Sponsor
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10,000+ employees
Founded 1993
🤖 Artificial Intelligence
🎮 Gaming
Artificial Intelligence • Gaming • Automotive
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.
• 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
• 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.
• equity • benefits
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