AI TLM Performance Modeling

Qualcomm

Confirmed live today High trust

Quick summary

Work type: On-site
Location: San Diego, CA
Salary: $162,000–$243,000 / yr
Posted: 32 days ago
Freshness: Confirmed live today
Closes: Mar 24, 2027
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $212k

This role $202k

$150k $274k

below market most similar roles pay here above market

This role pays less than 61% of similar roles. Most pay $177,300–$246,150 — the blue band above. At the midpoint, this role pays about $202k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 575 open roles on FindRole.

Listed pay typically runs $147,900–$221,900 across 550 roles with salary data.

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At a glance

TL;DR · AI TLM Performance Modeling

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The AI TLM Performance Modeling role sits within the Machine Learning Engineering group. You will join a multi-disciplinary team of hardware and system engineers to build performance modeling platforms and tools for Qualcomm’s SoC hardware. Your daily responsibilities include designing, developing, and testing platforms to analyze and optimize AI workloads, specifically aiming to improve performance and power efficiency across devices. You will work on finding optimal hardware architectures and tradeoffs for cloud data server applications. Key technical requirements include proficiency in Python, C/C++, SystemC, and TLM2.0. You must possess experience in SoC architecture, DDR memory controllers, NOC design, and ML networks including LLMs. Required skills also include TensorFlow, Pytorch, and compiler frameworks like LLVM or GCC to solve complex hardware acceleration problems.

Skills

Python C/C++ SystemC TLM2.0 TensorFlow PyTorch LLVM GCC SoC Architecture DDR Memory Controller NoC Design RTL DSP Architecture Machine Learning Performance Modeling

What you'll do

Build performance modeling platforms and tools for Qualcomm’s SoC hardware.
Analyze and validate LLMs and AI workloads for cloud data server applications.
Perform performance modeling to identify optimal hardware architectures and tradeoffs.
Optimize LLM frameworks and AI workloads for improved performance and power efficiency.
Design, develop, and test performance modeling platforms for analyzing AI workloads.
Measure and analyze the performance of machine learning networks.

What we're looking for

Bachelor's degree in a related field and 4+ years of engineering experience.
Master's degree in a related field and 3+ years of engineering experience.
PhD in a related field and 2+ years of engineering experience.
Proficiency in programming with Python, C/C++, SystemC, and TLM2.0.
Experience in SoC architecture, DDR memory controller, and NOC design/modeling.
Experience in AI workloads, architectures, and machine learning hardware accelerators.
Experience with TensorFlow, Pytorch, and compiler frameworks such as LLVM or GCC.
Familiarity with computer architecture, DSP architecture, and hardware RTL design/modeling/verification.

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