Senior DGX Cloud AI Infrastructure Software Engineer

🕒 February 3

🏄 California, Oregon, +2 more states – Remote

🏄 California – Remote 🌲 Oregon – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

🗣️ LLM Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

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.

📋 Description

• Develop infrastructure software and tools for large-scale pre-training, post-training, and inference. • Develop and optimize tools and libraries to improve infrastructure efficiency and resiliency. • Co-design and implement APIs for integration with NVIDIA's resiliency stacks. • Enhance infrastructure and products underpinning NVIDIA's AI platforms. • Define meaningful and actionable reliability metrics to track and improve system and service reliability. • Skilled in problem-solving, root cause analysis, and optimization. • Root cause and analyze and triage failures from the application level to the hardware level.

🎯 Requirements

• Minimum of 8+ years of experience in developing software infrastructure for large scale AI systems. • Bachelor's degree or higher in Computer Science or a related technical field (or equivalent experience). • Strong debugging skills and experience in analyzing and triaging AI applications from the application level to the hardware level. • Experience with observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki). • Proven track record in building and scaling large-scale distributed systems. • Experience with AI training and inferencing infrastructure services. • Proficiency in programming languages such as Python, C/C++, script languages. • Experience in quality software engineering practices, including test development, defensive programming, version control, and CI. • Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

🏖️ Benefits

• equity • benefits