Senior HPC Architect / HPC Program Lead

Applied Materials • Santa Clara, CA

10d • $140,500 - $193,000

About The Position

Applied Materials is seeking an experienced HPC technical lead to design, implement, and optimize high-performance computing environments. This hands-on technical role builds and maintains scalable, secure, high-performing HPC platforms across on-premises, cloud, and hybrid environments. The role serves as a technical expert for HPC infrastructure, cloud HPC platforms, schedulers, and AI/ML workloads, working with engineering teams, application users, IT operations, and vendors to address complex technical problems and meet platform performance and reliability requirements.

The role covers global HPC infrastructure, cloud HPC, AI/GPU platforms, engineering applications, and technical operations. It provides technical guidance to team members and contributes to architecture, solution design, platform operations, troubleshooting, performance optimization, and technical delivery. The position is based in Santa Clara, California, offers a stated salary range of $140,500 to $193,000, and requires travel 10% of the time. Relocation is not available.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
• At least 8 years of hands-on experience in HPC engineering, infrastructure, or architecture roles.
• At least 2 years of experience in a technical lead or senior engineer role.
• Strong hands-on knowledge of HPC cluster design, deployment, and administration.
• Strong hands-on knowledge of Linux system administration and performance tuning.
• Strong hands-on knowledge of Slurm or equivalent HPC workload schedulers.
• Strong hands-on knowledge of cloud HPC solutions, including Azure and AWS.
• Strong hands-on knowledge of parallel file systems and high-performance storage, such as Lustre, GPFS, BeeGFS, or Weka.
• Strong hands-on knowledge of high-speed networking, including InfiniBand and RDMA.
• Strong hands-on knowledge of GPU computing, including NVIDIA GPUs and CUDA.
• Strong hands-on knowledge of MPI and parallel application environments.
• Strong scripting and automation skills in Python, Bash, and PowerShell.
• Experience with infrastructure-as-code and configuration management tools such as Terraform, Ansible, or similar.
• Strong troubleshooting, analytical, and communication skills.

Nice To Haves

• Experience supporting engineering simulation and scientific workloads in enterprise HPC environments.
• Hands-on knowledge of CAE and CFD applications such as Ansys, Siemens, or similar tools.
• Experience with containers for HPC and AI, including Apptainer/Singularity, Docker, and Kubernetes.
• Experience with cloud-native AI platforms and MLOps workflows.
• Familiarity with HPC security, compliance, and governance frameworks.
• Relevant certifications in cloud technologies such as Azure or AWS, or in HPC environments.

Responsibilities

• Design, build, and optimize HPC clusters across on-premises, cloud, and hybrid environments.
• Translate the HPC roadmap into technical designs, implementation plans, and working solutions.
• Evaluate and conduct proof-of-concepts for HPC, GPU, and cloud technologies, and share technical recommendations.
• Define and follow technical standards, reference architectures, and best practices for HPC environments.
• Work with engineering, R&D, and AI/ML users to understand workload, application, and performance requirements.
• Translate requirements into technical designs, cluster configurations, and deployment approaches.
• Conduct technical feasibility assessments, design reviews, and benchmarking for new HPC use cases.
• Serve as the senior technical point of contact for HPC-related issues and solutions.
• Design and support GPU-accelerated infrastructure for AI/ML training and inference workloads.
• Tune GPU clusters, drivers, CUDA libraries, and containers for performance and stability.
• Work with AI/ML teams to optimize job scheduling, resource allocation, and data pipelines.
• Explore and prototype generative AI and emerging technologies on HPC platforms.
• Implement and maintain cloud HPC solutions on Azure, AWS, and other providers.
• Configure and manage HPC platforms such as Rescale, Azure CycleCloud, Slurm, and related tools.
• Automate cluster provisioning and configuration using infrastructure-as-code and scripting.
• Ensure HPC environments meet security, compliance, and business continuity requirements.
• Monitor cloud resource usage and recommend technical cost optimizations.
• Act as the highest-level escalation point for complex HPC incidents and troubleshooting.
• Perform performance tuning, benchmarking, and capacity analysis for compute, storage, and network.
• Drive root cause analysis and implement permanent fixes for recurring issues.
• Contribute to change management, patching, upgrades, and platform reliability improvements.
• Create and maintain technical documentation, runbooks, and knowledge articles.
• Provide technical mentoring and guidance to HPC engineers and support staff.
• Conduct code, configuration, and design reviews.
• Work with vendors and cloud providers on technical issues, product evaluations, and escalations.
• Coordinate technical delivery with infrastructure, storage, networking, security, and application teams.

Benefits

• Comprehensive benefits package.
• Candidates may be eligible for participation in a bonus and a stock award program, as applicable.
• Programs and support intended to encourage personal and professional growth and employee health and wellbeing.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior