Job Description

The ideal candidate will be responsible for designing, defining, implementing, and enabling comprehensive benchmark tests for AI infrastructure platforms, including box-level GPU systems, multi-GPU servers, and GPU rack-scale deployments. This role requires a strong understanding of AI workloads, system architectures, and performance characterization methodologies across modern AI infrastructure environments.

The individual will work closely with Marketing, Product Management and System Architecture teams to understand benchmark requirements and translate business and customer use cases into measurable performance validation strategies. The candidate will develop benchmark proposals, define evaluation methodologies, and execute performance studies for a wide range of AI applications, including Chat Assistants and LLM inference, Retrieval-Augmented Generation (RAG), Speech AI, Vision AI, multimodal AI, recommendation systems, and Image/Video Generation workloads.

Responsibilities include selecting and optimizing benchmark frameworks, configuring AI software stacks, validating hardware and software performance, analyzing bottlenecks across compute, memory, storage, and networking subsystems, and generating detailed performance reports with actionable insights. The candidate will evaluate AI workloads across different hardware configurations such as GPUs, CPUs, accelerators, high-speed interconnects, NVLink/NVSwitch fabrics, storage architectures, and network fabrics to compare scalability, latency, throughput, power efficiency, and cost-performance metrics.

The role also involves collaborating with internal and external partners to enable emerging AI models, benchmark suites, and infrastructure technologies, while ensuring reproducibility, automation, and continuous benchmarking capabilities within AI lab environments. Strong analytical, scripting, and performance tuning skills are essential, along with hands-on experience in AI frameworks, GPU computing, distributed inference environments, and performance monitoring tools.

Essential Duties and Responsibilities:
• Design & Validate AI Infrastructure for Benchmarks
• Analysis of Benchmarks for End-to-end AI Infrastructure and develop test environment for Benchmark tests
• Define and Perform Benchmark tests for AI workloads on storage systems
• Evaluate GPU vs CPU vs storage bottlenecks in AI pipelines
• Research and innovate Benchmarks for AI workloads on storage specific to Inference & training for major models
• Design Benchmarks for Vector DB & KV cache
• Optimize Data pipelines for Inference and training
• Analyze Benchmark results, document and publish with recommendations
Research and implement innovative ways to validate PCIe/NVMe SSD debug infrastructure.
Work with cross-functional teams for POC and architecture discussions for validation infrastructure.

Qualifications

Required:

• Bachelor's degree in Computer Science or Computer Engineering with 5+ years of experience, or a Master's degree in Computer Science or Computer Engineering with 2+ years of experience.

Skills:

• Experience with different Operating Systems (Windows, Linux, VMware).
• Scripting and/or programming languages, such as Shell scripts, Python, C/C++ are required.
• AI Infrastructure & Hardware Awareness - GPU/CPU architecture basics
• Experience in Performance & Benchmarking - profiling tools, system bottlenecks
• Debugging knowledge on performance bottlenecks in AI pipelines
• Experience in deriving data movement costs on Edge platforms

Compensation & Benefits Details

• An employee's pay position within the salary range may be based on several factors including but not limited to (1) relevant education; qualifications; certifications; and experience; (2) skills, ability, knowledge of the job; (3) performance, contribution and results; (4) geographic location; (5) shift; (6) internal and external equity; and (7) business and organizational needs.
• The salary range is what we believe to be the range of possible compensation for this role at the time of this posting. We may ultimately pay more or less than the posted range and this range is only applicable for jobs to be performed in California, Colorado, New York or remote jobs that can be performed in California, Colorado and New York. This range may be modified in the future.
• You will be eligible to participate in Sandisk's Short-Term Incentive (STI) Plan, which provides incentive awards based on Company and individual performance. Depending on your role and your performance, you may be eligible to participate in our annual Long-Term Incentive (LTI) program, which consists of restricted stock units (RSUs) or cash equivalents, pursuant to the terms of the LTI plan. Please note that not all roles are eligible to participate in the LTI program, and not all roles are eligible for equity under the LTI plan. RSU awards are also available to eligible new hires, subject to Sandisk's Standard Terms and Conditions for Restricted Stock Unit Awards.
• We offer a comprehensive package of benefits including paid vacation time; paid sick leave; medical/dental/vision insurance; life, accident and disability insurance; tax-advantaged flexible spending and health savings accounts; employee assistance program; other voluntary benefit programs such as supplemental life and AD&D, legal plan, pet insurance, critical illness, accident and hospital indemnity; tuition reimbursement; transit; the Applause Program, employee stock purchase plan, and the Sandisk's Savings 401(k) Plan.
• Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company's sole discretion, consistent with the law.