Senior Engineer, Machine Learning

Qualcomm

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
San Diego, CA
Salary
$140,800–$211,200 / yr
Posted
72 days ago
Freshness
Confirmed live 2 days ago
Closes
Dec 28, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k
This role $176k
$126k most similar roles pay here $277k

This role pays less than 74% of similar roles. Most pay $175,512–$247,216 — the shaded band above. At the midpoint, this role pays about $176k versus about $211k 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 623 open roles on FindRole.

Listed pay typically runs $148,300–$222,500 across 603 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · Senior Engineer, Machine Learning

Role Posting Log in to save

As a Senior Engineer - Machine Learning within the Machine Learning Engineering group, you will design, develop, and optimize machine learning systems to power next-generation AI platforms and applications. You will build scalable training, evaluation, and deployment workflows while developing reusable components, libraries, and frameworks. Your daily work involves optimizing model inference for latency and throughput using techniques like quantization, caching, and batching, as well as designing data pipelines for feature engineering and validation. You will integrate LLMs into APIs and microservices while managing serving infrastructure like vLLM or ONNX. The role requires proficiency in Python and systems languages like C++, Rust, or Go, alongside experience with PyTorch, TensorFlow, Kubernetes, and Docker. You will solve complex problems involving transformer architectures, RAG pipelines, and cost-aware system designs for production-grade AI capabilities across diverse hardware environments.

What does a Engineer earn in California?

Median $208000 from 94 postings across 22 companies.

See salary data

Skills

Python C++ Rust Go PyTorch TensorFlow LLM Transformer vLLM ONNX Kubernetes Docker CI/CD RAG Vector Databases OpenSearch Qdrant Quantization Distributed Computing Microservices

What you'll do

  • Design and implement machine learning models and pipelines for production use.
  • Build scalable training, evaluation, and deployment workflows.
  • Optimize model inference for latency, throughput, and cost using quantization, caching, and batching.
  • Benchmark and profile models across diverse workloads and hardware environments.
  • Integrate ML and LLM models into APIs, microservices, and applications.
  • Maintain model-serving infrastructure such as vLLM, ONNX, and custom runtimes.
  • Design data pipelines for ingestion, preprocessing, feature engineering, and validation.
  • Develop reusable machine learning components, libraries, and frameworks.

What we're looking for

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field with 2+ years of relevant engineering experience.
  • Master's degree in Computer Science, Engineering, Information Systems, or a related field with 1+ year of relevant engineering experience.
  • PhD in Computer Science, Engineering, Information Systems, or a related field.
  • Proficiency in Python and at least one systems language such as C++, Rust, or Go.
  • Strong understanding of machine learning fundamentals, transformer architectures, LLMs, and model evaluation.
  • Experience with ML frameworks like PyTorch or TensorFlow and experience building scalable software and APIs.
  • Experience with LLMs, multimodal models, generative AI, RAG pipelines, and distributed computing in GPU/accelerator environments.
  • Knowledge of model optimization (quantization, distillation), vector databases, and containerization tools like Kubernetes and Docker.

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