Full-Time

AI/ML ASIC Architect

Sandisk

Sandisk

1,001-5,000 employees

Develops non-volatile flash memory storage devices

No salary listed

Milpitas, CA, USA

Hybrid

Category
Hardware Engineering (1)
Required Skills
LLM
Requirements
  • Bachelors or Masters or PhD in Computer/Electrical Engineering with 15+ years of hands-on Architecture experience authoring specifications
  • Strong technical background architecting ASIC, SoC, or I/O subsystems involving PCIe/UCIe/CXL and DMA engines
  • Knowledge of I/O Subsystem and DMA interactions with internal embedded processor-subsystems (x86, RISC-V or ARM) and external host CPU
  • Good understanding of computer/graphics architecture, ML, LLM
  • Architecting a GPU/TPU/xPU Accelerator systems with optimized high bandwidth memory hierarchy and frontend architecture for multi-trillion parameter LLM training/inference including Dense, Mixture of Experts (MoE) with multiple modalities (text, vision, speech)
  • KV cache optimization, Flash Attention, Mixture of Experts
  • Deep experience optimizing large-scale ML systems, GPU architectures
  • Proficiency in principles and methods of microarchitecture, software, and hardware relevant to performance engineering
  • Knowledge of ARM Processors and AXI Interconnects
Responsibilities
  • Responsible for driving the AI/ML ASIC architecture that integrates the AI Storage with GPU/TPU/xPU accelerators, with a particular focus on I/O subsystems connected over UCIe/ PCIe/CXL
  • Author architecture specifications in clear and concise language for AI/ML xPU based Accelerator using AI Storage Solutions.
  • Define I/O subsystem and PCIe DMA architectures, including their interactions with internal embedded processor-subsystems, Network on Chip, Memory controllers, and FPGA fabric.
  • Create flexible and modular I/O subsystem architectures that can be deployed in either Chiplet, monolithic or 3D form factors.
  • Work with customers, and cross-functional teams to scope SoC requirements, analyze PPA tradeoffs, and then define architectural requirements that meet the PPA and schedule targets.
  • Define SoC subsystem and DMA hardware, software, and firmware interactions with embedded processing subsystems and SoC CPUs on the device side and Host CPUs.
  • Author architecture specifications in clear and concise language. Guide and assist pre-silicon design/verification and post-silicon validation during the execution phase.
  • Responsible for improving the AI/ML ASIC Architecture performance through hardware & software co-optimization, post-silicon performance analysis, and influencing the strategic product roadmap.
  • Work with customers, and cross-functional teams to scope SoC requirements, analyze PPA tradeoffs, and then define architectural requirements that meet the PPA and schedule targets.
  • Guide and assist pre-silicon design/verification and post-silicon validation during the execution phase.
  • LLM Workload analysis and characterization of ASIC and competitive datacenter and AI solutions to identify opportunities for performance improvement in our products.
  • Experience architecting one or some components of AI/ML accelerator ASICs such as HBM, PCIe/UCIe/CXL, NoC, DMA, Firmware Interactions, NAND, xPU, fabrics, etc
  • Drive the AI Storage Solutions frontend system architecture with GPU/TPU/NPU/xPU to match or exceed the nextgen HBM bandwidth
  • Architect memory-efficient inference/training systems utilizing techniques like pruning, quantization with MX format , continuous batching/chunked prefill, and speculative decoding
  • Collaborate with internal and external stakeholders/ML researchers to disseminate results and iterate at rapid pace
Desired Qualifications
  • Familiarity and background in UCIe, CXL, NVLink, or UAL microarchitecture and protocols is a plus
  • Familiarity with High-speed networking: InfiniBand, RDMA, NVLink is a plus
  • Expert knowledge of transformer architectures, attention mechanisms, and model parallelism techniques
  • Multi-disciplinary experience, including familiarity with Firmware and ASIC design
  • Expertise in CUDA programming, GPU memory hierarchies, and hardware-specific optimizations
  • Proven track record architecting distributed training systems handling large scale systems
  • Previous experience with NVMe storage systems, protocols, and NAND flash – advantage

SanDisk designs solid-state storage products based on flash memory, a non-volatile technology that preserves data without power. Its offerings include memory cards (CompactFlash, SD) and USB flash drives, using controllers and firmware to manage read/write, error correction, and wear leveling for durable, portable storage. The company helped popularize flash memory for cameras and mobile devices and expanded production to meet growing demand. In 2016, Western Digital acquired SanDisk for about $19 billion, combining flash expertise with HDD leadership to provide a broader range of storage solutions.

Company Size

1,001-5,000

Company Stage

Acquired

Total Funding

$19B

Headquarters

Milpitas, California

Founded

1988

Simplify Jobs

Simplify's Take

What believers are saying

  • Q3 2026 revenue hit $5.95B, up 251% YoY from AI datacenter demand.
  • $42B multi-year AI supply deals secure over third of FY2027 output.
  • Debt-free with $4.5B free cash flow funds $6B share buyback.

What critics are saying

  • Micron floods market with NAND by Q1 2027, slashing SanDisk prices.
  • Samsung undercuts $42B hyperscaler deals using integrated DRAM-NAND in 2027.
  • Nvidia Blackwell GPUs cut NAND demand 30% in data centers by mid-2027.

What makes Sandisk unique

  • SanDisk invented Floating Gate EEPROM in 1988, enabling practical flash memory.
  • SanDisk delivered first 20MB 2.5-inch SSD to IBM in 1991.
  • SanDisk pioneered CompactFlash in 1994 and SD cards in 1999.

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Benefits

Hybrid Work Options

Remote Work Options

Flexible Work Hours

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Home Office Stipend

Professional Development Budget

Conference Attendance Budget

Wellness Program

Mental Health Support

Stock Options

Company Equity

401(k) Retirement Plan

401(k) Company Match

Health Insurance

Dental Insurance

Vision Insurance

Paid Vacation

Paid Sick Leave

Paid Holidays

Parental Leave

Family Planning Benefits

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Employee Discounts

Gym Membership

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Tuition Reimbursement

Company News

Yahoo Finance
Apr 2nd, 2026
Sandisk surges 1,200% to become S&P 500's top performer since Liberation Day tariffs

Sandisk has been the S&P 500's top performer since President Trump's "Liberation Day" tariff announcement a year ago, surging 1,200%. The company spun off from Western Digital in February last year to focus on flash memory, benefiting from strong artificial intelligence demand. In its most recent quarter ending 2 January, Sandisk's revenue rose 61% year-over-year to $3 billion, whilst net income jumped from $104 million to $803 million. The company expects revenue could reach $4.8 billion in the current quarter. Despite the rally, Sandisk trades at less than 13 times forward earnings, well below the S&P 500 average of 20. Analysts remain optimistic due to ongoing memory and storage product shortages.

Yahoo Finance
Apr 2nd, 2026
Sandisk soars 9% ahead of earnings, revenues expected to more than double to $4.8B

Sandisk Corp. shares surged 9.03% to $692.73 on Wednesday as investors positioned ahead of the company's third-quarter earnings announcement scheduled for 30 April. The flash memory manufacturer is expected to report revenues between $4.4 billion and $4.8 billion, representing growth of 159% to 182% from $1.7 billion in the same quarter last year. Non-GAAP diluted earnings per share are projected at $12 to $14, reversing a $0.30 loss per share from the prior year. Gross margin is forecast between 64.9% and 66.9%. Earlier this year, Sandisk partnered with SK hynix on High Bandwidth Flash, a next-generation memory solution designed for AI inference workloads, addressing the industry's shift from model training to delivering AI services.

Yahoo Finance
Mar 29th, 2026
Google's TurboQuant AI compression tech hits SanDisk stock with memory demand concerns

Sandisk shares sold off following Google's introduction of TurboQuant, an AI compression technology that could significantly reduce memory requirements for AI models. The announcement prompted investors to reassess long-term demand assumptions for memory-related stocks. TurboQuant directly impacts Sandisk's core business of flash storage products serving data centres, PCs and mobile devices. The memory industry has been closely tied to AI infrastructure buildouts, where demand for fast, dense storage has been a key growth driver. Trading at $615.83, Sandisk's shares are approximately 20% below the analyst target of $770.32. The stock recorded a 30-day return of -3.07% following the news. Debate continues over whether more efficient compression might ultimately expand AI usage overall, potentially supporting memory volumes through increased model counts.

Yahoo Finance
Mar 26th, 2026
Two semiconductor stocks to buy before the memory supercycle peaks with $2,000

Micron Technology has been identified as a semiconductor stock to consider buying during the current memory supercycle. The company, one of three major DRAM producers alongside SK Hynix and Samsung, generates approximately 80% of revenue from DRAM and the remainder from NAND memory. Demand for high bandwidth memory has created supply constraints across the DRAM market, driving prices higher. Last quarter, Micron's revenue surged nearly threefold to $23.9 billion, whilst gross margins jumped to 74.4% from 36.8% year-over-year. The company projects margins will reach 81%. Despite strong performance, Micron trades at a forward P/E of four times fiscal 2027 estimates due to the memory market's historically cyclical nature. However, the company is securing longer contracts, including a five-year deal, providing greater revenue visibility.

Yahoo Finance
Mar 25th, 2026
Google's TurboQuant algorithm rattles memory stocks with 6x compression breakthrough

Memory stocks fell Wednesday after Google unveiled TurboQuant, a compression algorithm that could reduce memory requirements for AI systems. SanDisk dropped 5.7%, Micron Technology fell 3%, Western Digital declined 4.7%, and Seagate Technology slid 4%, despite broader technology sector strength. TurboQuant compresses key-value cache in large language models to 3 bits without requiring training, whilst maintaining accuracy. Testing on open-source models including Gemma and Mistral showed a 6x reduction in memory size and up to 8x performance increase on H100 GPU accelerators. The technology uses PolarQuant compression and the Quantized Johnson-Lindenstrauss algorithm to eliminate errors. Google will present the findings at ICLR 2026 and AISTATS 2026. Memory stocks have rallied significantly year to date, making them vulnerable to demand-reducing developments.