Senior AI Infrastructure Engineer – DGX Cloud

October 24

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Logo of NVIDIA

NVIDIA

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.

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

📋 Description

• Build AI-powered tools that enhance operational excellence by leveraging diverse operational data, supporting incident, change, and problem management workflows • Collaborate closely with Incident Commanders, incident response, and SRE teams to integrate AI-driven automation and analytics into operational workflows • Design, develop, and maintain backend systems and infrastructure using Go and Python to support internal AI tools and intelligent agents • Build and maintain data pipelines using PySpark and related tools to support AI and analytics workflows • Operate and scale infrastructure using Kubernetes, managing containerized AI services and automating pipeline deployments • Work with vector databases to enable semantic search and retrieval-augmented generation use cases • Integrate large language models, agent systems, and classical ML models into internal services and automation workflows • Improve observability, deployment automation, and system reliability for AI-driven services

🎯 Requirements

• 8+ years of software engineering experience, with deep expertise in backend systems and infrastructure. • Bachelor's degree or equivalent experience. • Strong proficiency in Python and Go, with a track record of delivering reliable, scalable software solutions • Experience designing scalable, maintainable backend systems and writing clear design documentation • Deep experience with Kubernetes and cloud-native infrastructure • Experience working with building, deploying, and maintaining ML models in production systems • Familiarity with AI agent frameworks or orchestration tools • Solid understanding of system observability, monitoring, and performance optimization • Strong collaboration and communication skills to work across remote teams

🏖️ Benefits

• Eligible for equity and benefits

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