Senior Engineer

🕒 July 23

🏄 California, Washington – Remote

🏄 California – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

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

• develop innovative solutions that advance AI infrastructure capabilities. • directly influence customer success with breakthrough AI initiatives. • build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures. • act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines. • deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds. • profile and tune large-scale training and inference workloads on NCP platforms. • implement observability and SLO/SLA monitoring. • lead detailed efforts to reduce latency, cost, and operational risk. • implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity. • build detailed implementation guides, runbooks, and post‑mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.

🎯 Requirements

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience. • 8+ years of experience in customer facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large‑scale cloud or service provider environments. • Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms. • Demonstrated AI/ML experience supporting large‑scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments. • Solid programming skills in Python/Go, with hands‑on experience using frameworks such as PyTorch or TensorFlow for training and serving. • Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution. • Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade‑offs, and recommendations to both engineering and leadership audiences.

🏖️ Benefits

• equity • benefits