Note: The job is a remote job and is open to candidates in USA. NVIDIA is a technology company advancing artificial intelligence, high-performance computing, and visualization. The Senior AI Infrastructure Software Engineer will design, build, and maintain scalable AI platforms and infrastructure services supporting large-scale training, inferencing, fine-tuning, and Agentic AI in production. The role also focuses on workload efficiency, resiliency, reliability metrics, failure analysis, and API integration.
Responsibilities
- Develop platform and tools for large-scale AI, LLM, and GenAI infrastructure
- Develop and optimize tools to improve AI/ML workload efficiency and resiliency
- Root cause and analyze and triage failures from the application level to the hardware level
- Enhance infrastructure and products underpinning NVIDIA's AI platforms
- Co-design and implement APIs for integration with NVIDIA's resiliency stacks on the platform
- Define meaningful and actionable reliability metrics to track and improve system and service reliability
- Skilled in problem-solving, root cause analysis, and optimization
Skills
- 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
- Proven track record in building and scaling large-scale distributed systems
- Experience with AI training and inferencing and data infrastructure services
- Familiar in Kubernetes and operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki)
- Proficiency in programming languages such as Golang, Python, C/C++, script languages
- Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential
- Experience in working with the large scale AI cluster and cloud-native infrastructure
- Strong understanding of NVIDIA GPUs, network technologies (RDMA, IB, NCCL)
- Good understanding on DL frameworks internal PyTorch, TensorFlow, JAX, Dynamo, and Ray
- Experience and root cause analysis of failures and datacenter scale
- Strong background in software design and development
Benefits
- Eligible for equity
- Benefits
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