To make electronics, you need chips, wafers, transistors, reticles, and... To make these, you must see, test and manufacture them at scale—faster and better than ever before. That's where KLA comes in. Whether you're early in your career or an experienced professional, you'll solve complex challenges, work alongside brilliant minds and help shape the future of technology.

Group/Division

What You'll Do

In this role, you will play a key part in advancing business priorities by delivering high-impact work across your area of expertise.

Preferred Qualifications

We are seeking a highly skilled Sr. Software Engineer with specialized expertise

Design, build, and operate production-grade AI infrastructure for large-scale GPU training and inference. The role owns cluster architecture from ground zero, distributed workload orchestration, accelerator management, performance engineering, and open-source integration. TPU experience is optional. 

Key Responsibilities 

• Design and deploy scalable, multi-node GPU clusters on Kubernetes, including compute, networking, storage, scheduling, security, and observability. 

• Build distributed training and reinforcement learning platforms using Ray and NVIDIA NeMo RL, supporting frameworks such as PyTorch and JAX. 

• Deploy and optimize high-throughput LLM inference using vLLM, SGLang, and NVIDIA Dynamo. 

• Implement GPU scheduling, quotas, isolation, autoscaling, health monitoring, and capacity management for multi-tenant environments. 

• Profile and troubleshoot GPU workloads using NVIDIA Nsight Systems, Nsight Compute, DCGM, CUDA, NCCL, and related diagnostics. 

• Automate cluster provisioning, upgrades, workload deployment, and operational recovery through infrastructure-as-code and GitOps practices. 

• Contribute to or actively participate in relevant open-source AI infrastructure communities and bring upstream best practices into the platform. 

Minimum Qualifications

• ​Bachelor's Degree and eight (8) years of Software Engineering experience

• Four (4) years in software, cloud, platform, HPC, or infrastructure engineering, including two (2) years supporting distributed AI/ML workloads. 

• Proven hands-on experience building GPU clusters from the ground up and operating them at production scale. 

• Deep Kubernetes expertise, including operators, CRDs, Helm, networking, storage, scheduling, and cluster lifecycle management. 

• Production experience with Ray and at least two of the following: NVIDIA NeMo RL, vLLM, SGLang, or NVIDIA Dynamo. 

• Strong knowledge of NVIDIA GPUs, CUDA, NCCL, GPU Operator, DCGM, MIG, RDMA, and multi-node collective communication. 

• Experience debugging training and inference performance across GPU, CPU, memory, network, and storage layers. 

• Proficiency in Python and Linux, plus experience with containers, CI/CD, GitOps, infrastructure-as-code, and platform observability. 

• Demonstrated open-source contribution, maintainership, or meaningful participation in an AI infrastructure project. 

Preferred Qualifications 

• Experience with Google TPUs and TPU-oriented frameworks or distributed workloads. 

• Experience with large language model training, fine-tuning, RLHF or agentic reinforcement learning. 

• Knowledge of TensorRT-LLM, Triton Inference Server, DeepSpeed, Megatron-LM, or similar performance-oriented frameworks. 

• Experience operating secure, multi-tenant AI platforms in enterprise or regulated environments. 

About KLA

We provide advanced inspection tools, metrology systems, process solutions, and computational analytics that make electronics possible, tackling complex challenges. From electron and photon optics to machine learning and data analytics, we seek perfection at the most fundamental level of matter in the universe. If you want to make electronics that push industries forward and make the world a better place, join us.

Total Rewards

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.

Use of AI Statement 

At KLA, our interviews seek to understand your individual skills, problem-solving approach and authentic thinking. To ensure a fair and consistent evaluation, the use of AI, recording tools or other technologies to generate, suggest or provide responses during interviews—whether virtual or in person—is not permitted unless explicitly approved in advance as part of a reasonable accommodation or invited by the interviewer. Use of these tools may interfere with our ability to evaluate your individual qualifications and affect your candidacy. KLA is committed to advancing innovation through responsible AI, and we value candidates who share this mindset.

Equal Opportunity Statement

KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us at [email protected] or at +1-408-352-2808 to request accommodation.

For additional information, view the US Know Your Rights poster on the U.S. Equal Employment Opportunity Commission website.