Job Description/Preferred Qualifications

Key Responsibilities

HPC Software Engineering
• Design, develop, and optimize HPC software running on large-scale Linux clusters, including distributed and parallel workloads (MPI, multithreading, GPU-accelerated pipelines, containerized workloads).
• Optimize application performance and power utilization across CPU, memory, storage, and network subsystem, with attention to throughput, latency, and scaling behavior.
• Develop and maintain system-level tooling for cluster bring-up, diagnostics, monitoring including component power usages, and health checks.
• Work closely with algorithms, systems and application teams to understand and translate workload characteristics into power-efficient HPC software solutions.

HPC Systems & Hardware Awareness
• Collaborate with hardware and systems teams to define HPC node, storage, and interconnect requirements based on software and algorithm needs.
• Understand and influence CPU/GPU selection, memory sizing, PCIe layout, NUMA behavior, and network topology to ensure optimal software performance.
• Participate in HW/SW co-debug activities, including performance bottlenecks, stability issues, and failure analysis.

Rack & Infrastructure Engineering
• Understand rack-level integration of HPC systems, focusing on power, cooling, cabling, networking, and physical layout considerations.
• Understand data-center and lab constraints such as power budgets, thermal limits, network drops, and serviceability.
• Contribute to best practices, and design reviews for new platforms and refresh cycles.

Cross-Functional Collaboration
• Act as a technical bridge between software, hardware, systems teams.
• Provide clear technical documentation covering software and system architecture, deployment flows, performance assumptions.

Required Qualifications
• Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
• Strong experience developing HPC or systems software on Linux.
• Proficiency in Java and/or C++ and/or other system-level or performance-oriented languages.
• Hands-on experience with parallel computing (MPI, OpenMP, multithreading). Candidates with GPU computing (CUDA, ROCm, or equivalent) would be preferred.
• Solid understanding of HPC hardware fundamentals: CPUs, memory hierarchies, storage, networking (Ethernet / InfiniBand).
• Practical experience working with clusters, servers, or rack-scale systems in lab or production environments.
• Strong debugging skills across software, OS, and hardware boundaries.

Preferred Qualifications
• Experience with containerized HPC environments (Docker, Singularity/Apptainer, Kubernetes in HPC contexts).
• Familiarity with high-speed interconnects, storage architectures, and performance benchmarking.
• Exposure to rack integration, including cabling, power distribution, cooling, and system bring-up.
• Experience in semiconductor, manufacturing, or high-reliability systems environments.
• Ability to reason about system reliability, MTBF/MTBA, and failure modes in large compute installations.

What Makes This Role Unique at KLA
• Work on mission-critical HPC platforms that directly impact semiconductor manufacturing capability.
• Influence both software architecture and physical system design, not just code in isolation.
• Collaborate with world-class experts across algorithms, hardware, systems, and operations.
• See your work deployed at scale in real production tools-not just in the data center.

Minimum Qualifications

Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

Base Pay Range: $105,900.00 - $180,000.00 Annually

Primary Location: USA-MI-Ann Arbor-KLA

KLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.

Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.