CPU FP-SIMD Architect - High-Performance Datapaths, Equity

Google

Austin (TX)

On-site

USD 138,000 - 197,000

Full time

10 days ago
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Job summary

Google Austin is seeking a hardware engineer to join the CPU design team developing the first Google CPU and FP-SIMD datapaths aligned with IEEE 754, focusing on performance, clock and low power.

You will collaborate with architecture teams to define high-performance FP datapaths and SIMD paths, participate in RTL/physical implementation, and help shape next-generation hardware. Interviews are typically in-person, with options for preferred locations Austin or Mountain View.

Qualifications

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 4 years of experience with IEEE 754 datapath implementations including design, verification and physical implementation issues.
  • Experience with Floating Point and SIMD ISA.

Responsibilities

  • Create the first Google CPU for processor design team.
  • Define floating point data paths implementing the IEEE 754 standard while achieving performance, clock and low power goals.
  • Implement integer single instruction, multiple data (SIMD) and floating point SIMD data paths focusing on power/performance.
  • Work with architecture teams and other micro architects to define high performance floating point issue, register, bypass and retirement logic to support a complex FP-SIMD instruction set architecture (ISA).

Skills

IEEE 754 datapath
Floating point
SIMD ISA

Education

Bachelor's degree or equivalent practical experience

Job description

Google Austin is seeking a hardware engineer to join the CPU design team developing the first Google CPU and FP-SIMD datapaths aligned with IEEE 754, focusing on performance, clock and low power.

You will collaborate with architecture teams to define high-performance FP datapaths and SIMD paths, participate in RTL/physical implementation, and help shape next-generation hardware. Interviews are typically in-person, with options for preferred locations Austin or Mountain View.

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