Senior/Staff Software Engineer, LLM Inference Systems & Open-Source

Qualcomm

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CASan Diego, CA
Salary
$162,000–$243,000 / yr
Posted
20 days ago
Freshness
Confirmed live today
Closes
Apr 12, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $179k
This role $202k
$105k $258k
below market most similar roles pay here above market

This role pays more than 73% of similar roles. Most pay $149,500–$208,000 — the blue band above. At the midpoint, this role pays about $202k versus about $179k 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 587 open roles on FindRole.

Listed pay typically runs $147,900–$218,400 across 562 roles with salary data.

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At a glance

TL;DR · Senior/Staff Software Engineer, LLM Inference Systems & Open-Source

The Senior/Staff Software Engineer - LLM Inference Systems & Open-Source joins the Machine Learning Engineering team to advance the software ecosystem for large-scale LLM inference on Qualcomm platforms. You will contribute to open-source projects like llm-d by developing integrations for Qualcomm AI accelerators, focusing on distributed LLM serving, orchestration, and inference runtime integration. Daily responsibilities include developing device abstractions, memory management, and distributed execution while optimizing performance metrics like throughput and latency. You will utilize Python, C++, Go, or Rust to build cloud-native infrastructure using Kubernetes. Key technical tasks involve implementing model parallelism, KV-cache management, and request routing. This role solves the complex problem of building scalable, production-grade inference infrastructure by bridging the gap between hardware accelerators, distributed systems, and open-source LLM serving frameworks.

What does a Software Engineer earn in California?

Median $214500 from 1167 postings across 73 companies.

See salary data

What you'll do

  • Contribute features, bug fixes, and architectural enhancements to open-source LLM inference projects like llm-d.
  • Develop and improve support for Qualcomm AI accelerators within open-source LLM serving frameworks.
  • Design and implement distributed LLM inference capabilities including KV-cache management and model parallelism.
  • Integrate LLM inference software with Kubernetes and cloud-native infrastructure for scheduling and autoscaling.
  • Profile, benchmark, and optimize end-to-end inference performance metrics like throughput and latency.
  • Diagnose complex issues across model-serving frameworks, distributed runtimes, operating systems, and hardware.
  • Develop technical documentation, reference deployments, and best practices for customers deploying LLM workloads.

What we're looking for

  • Bachelor's degree in a related field with 4+ years of experience, Master's with 3+ years, or PhD with 2+ years of experience.
  • Bachelor's degree in a related technical field or equivalent practical experience.
  • Strong software engineering and debugging skills.
  • Experience developing production-quality software in Python, C++, Go, or Rust.
  • Strong understanding of machine learning, distributed systems, AI accelerators, cloud-native infrastructure, or ML compilers.
  • Experience debugging complex software systems across multiple layers of the stack.
  • Ability to collaborate effectively across teams and communicate technical concepts clearly.
  • Experience in LLM inference engines, distributed systems, PyTorch internals, or open-source development (preferred).

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