Samsung Semiconductor

Samsung Semiconductor

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Work type
On-site
Location
San Jose, CA
Posted
13 days ago

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How this pay compares to similar roles

Similar $208k
$160k most similar roles pay here $265k

This listing doesn't post a salary. Most similar roles pay $170,000–$246,150.

Based on 240 similar postings.

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About Samsung Semiconductor

Samsung Semiconductor is the global semiconductor business unit of Samsung Electronics, designing and manufacturing memory chips, logic semiconductors, and foundry solutions for a broad range of applications.

Samsung Semiconductor currently has 59 open roles on FindRole.

Listed pay typically runs $163,000–$253,000 across 51 roles with salary data.

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At a glance

TL;DR · Samsung Semiconductor

The Senior AI Systems Engineer role at AGICL lab within DSRA involves designing and optimizing high-performance Triton kernels for large language model (LLM) workloads on modern accelerators. This hands-on position requires daily analysis of kernel performance using profiling tools to identify bottlenecks and propose optimizations, working closely with hardware architects and compiler engineers to ensure end-to-end efficiency. Candidates should have extensive experience in writing high-performance Triton kernels, a deep understanding of LLM fundamentals, and proficiency in Python and low-level programming paradigms. Familiarity with FlashAttention, fused kernels, MoE kernels, and emerging domain-specific languages (DSLs) is essential. The role offers the opportunity to work on cutting-edge accelerator hardware and experimental software stacks, contributing to the design and optimization of next-generation AI systems.

What you'll do

  • Design, implement, and optimize high-performance Triton kernels for LLM workloads on accelerators.
  • Analyze kernel performance using profiling tools to identify memory access patterns and synchronization issues.
  • Propose concrete optimizations to address performance bottlenecks in kernel design.
  • Work with hardware architects and compiler engineers to co-design solutions spanning software and hardware boundaries.
  • Prototype and evaluate kernel optimizations using experimental domain-specific languages (DSLs) and compiler flows.

What we're looking for

  • Strong experience writing high-performance Triton kernels for GPUs or other accelerators.
  • Solid understanding of large language model fundamentals and transformer architectures.
  • Deep knowledge of accelerator hardware architecture, including memory hierarchies.
  • Proven ability to read and interpret profiling data and performance counters.
  • Experience diagnosing and resolving performance bottlenecks in kernel-level code.
  • Strong systems programming skills in Python and low-level performance-oriented paradigms.
  • Familiarity with emerging domain-specific languages (DSLs) for accelerator programming.

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