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AI Systems Engineer

San Jose, CA, United States

Job Overview: We are seeking an AI Systems Engineer to join our IT compute platforms engineering team. The AI Systems Engineer is responsible for the design, development, and administration of High-Performance Computing (HPC) infrastructure, GPU clusters, and AI workload schedulers.

ABOUT YOU:

You have a passion for learning. You are passionate about the field of large-scale distributed computing in AI and HPC workloads. You take responsibility for end-to-end outcomes of your efforts. You want to build scalable and highly performant HPC/AI/Data services with hardware, software, people and processes. You have a curiosity to learn and improve scalable HPC systems. You have significant experience in working across a globally distributed organization.

Responsibilities: Develop, implement, and maintain GPU-based clusters of 10 to 1000 nodes, ensuring optimal performance and availability.

Administer Client/AI platforms Distributed Client services, LLMs, Vector-DB and AI inferencing, by managing deployments, resource allocation, monitoring, and security.

Collaborate with cross-functional teams to address AI infrastructure requirements, support AI-related projects, and provide technical expertise.

Monitor and evaluate the performance of AI systems and clusters, ensuring that they adhere to industry best practices and meet company standards.

Compile reports, document procedures, and publish recommendations for improving AI infrastructure and solutions.

Use AI/Client to continuously improve internal processes and tools that are used in end-to-end delivery of your services in this team

Experience and Qualifications: 4+ years of experience in HPC infrastructure engineering for AI/HPC domain

2+ years of experience managing GPU clusters optimizing GPU-based services/tools/software

Experience in creating web services with HPC backend (like AI)

Proficiency in RoCEv2, K8s, KVM, Ubuntu, Python, Shell, Go, Rust, GPU drivers, and Cluster interconnect with 200G/400G networking.

Demonstrated experience with AI workload schedulers and allocation optimization.

Strong organizational, problem-solving, and troubleshooting skills, with the ability to manage multiple projects simultaneously.

Excellent verbal and written communication skills, with the ability to collaborate effectively with team members and stakeholders at all levels of the organization .

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