Director, AI Systems & Performance Lab

Sandisk; California (MO); On-site; USD 190,000 - 260,000; Full time

Benefits offered by this job

STI plan

LTI plan

Comprehensive benefits

401(k) plan

Job summary

Sandisk seeks a Sr. Technologist to lead an AI Systems & Performance Lab in Milpitas, CA. The role focuses on identifying AI bottlenecks across real-world workloads, software stacks, and diverse hardware configurations, shaping architecture and platform strategy.

Ideal candidates bring deep expertise in AI workloads and end-to-end system performance, plus the ability to translate findings into actionable recommendations and business impact. Strong leadership and communication are required.

Qualifications

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field; advanced degrees preferred.
• 15+ years of industry experience in systems engineering, AI infrastructure, performance engineering, or hardware/software co-design.
• Hands-on experience with AI workloads, including modern DL models and frameworks.

Responsibilities

• Establish and articulate a clear AI Lab vision and charter focused on AI workload characterization and performance bottleneck analysis.
• Drive end-to-end analysis of AI training and inference workloads across models, frameworks, runtimes, and system stacks.
• Develop benchmarking, profiling, and workload characterization frameworks for multiple hardware configurations.
• Collaborate with hardware, platform, and software teams to translate findings into design recommendations.
• Provide technical mentorship to a small team and influence executive decision-making with data-driven insights.

Skills

AI workloads

System performance

Hardware architecture

Technical leadership

Education

Bachelor's in Computer Engineering/CS/EE

Master's or PhD preferred

Tools

PyTorch

TensorFlow

JAX

Job description

Sandisk seeks a Sr. Technologist to lead an AI Systems & Performance Lab in Milpitas, CA. The role focuses on identifying AI bottlenecks across real-world workloads, software stacks, and diverse hardware configurations, shaping architecture and platform strategy.

Ideal candidates bring deep expertise in AI workloads and end-to-end system performance, plus the ability to translate findings into actionable recommendations and business impact. Strong leadership and communication are required.