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Engineer, Machine Learning Accelerator (MLA) Modeling (AI2432)

Engineer, Machine Learning Accelerator (MLA) Modeling (AI2432)

SiMa.aiSan Jose, CA, United States
4 days ago
Job type
  • Full-time
Job description

Overview

Sr. Engineer, Machine Learning Accelerator (MLA) Modeling (AI2432) at SiMa.ai. This position is on-site in San Jose, CA.

Job Number : AI2432

Responsibilities

  • Partner with the Architecture team to develop and maintain the performance and power analysis tool.
  • Adapt the tool to analyze key performance and power drivers in SiMa.ai’s MLA architecture for relevant neural networks like ViTs.
  • Coarsely model key IPs like the DMA / DRAM in the MLSoC to address performance and power issues.
  • Work with the MLSOc architecture team to optimize the performance of the SiMa.ai MLA : reduce local memory requirements, increase DMA throughput and overall efficiency.
  • Identify HW / SW trade-offs / enhancements and work with the compiler / tool chain team and silicon team to implement them in our next-generation products.
  • Contribute to the performance roadmap for SiMa.ai’s next-generation MLA architecture.
  • Research, scope, and analyze the interplay of hardware and software architectures in targeted applications.

Qualifications

  • MS or PhD in Computer Architecture, with at least 2 years of work experience
  • Strong understanding of machine learning architecture like systolic arrays
  • Background in CNN / ViT networks
  • Proficiency in Python and C++
  • Strong mathematical foundation in machine learning and deep learning
  • Job Details

  • Location : San Jose, CA (on-site)
  • Seniority level : Mid-Senior level
  • Employment type : Full-time
  • Job function : Engineering and Information Technology
  • Industries : Software Development
  • Compensation & EEO

    The annual salary for this position ranges from $140,000 to $194,000, based on factors including skills, experience, qualifications, location, and market conditions. SiMa is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status or any other protected classification.

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