below marketmost similar roles pay hereabove market
This role pays less than
58%
of similar roles. Most pay
$155,000–$235,487
— the blue band above.
At the midpoint, this role pays about
$176k
versus about
$195k
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.
The Senior / Engineer – AI Model Enablement & Software Tools joins the AI Stack SDK Software team to bring modern AI models to Snapdragon platforms. This role involves analyzing, adapting, optimizing, quantizing, compiling, and validating various models, including Large Language Models, vision models, and multimodal models. You will work with research and hardware teams to identify backend gaps, implement model re-authoring, and develop reusable support for model-enablement frameworks. Key responsibilities include converting models from PyTorch and ONNX, applying quantization and calibration flows, and debugging across software and hardware layers. Required skills include Python and C/C++, software engineering fundamentals, and experience with AI/ML concepts like neural networks and model inference. The work focuses on on-device execution, graph processing, and performance optimization for mobile and edge environments.
What does a Engineer earn in California?
Median $199500 from 103 postings across 31 companies.
Bring up and enable new language, vision, and multimodal models on Snapdragon platforms.
Analyze computational graphs to identify unsupported operators, precision constraints, and performance limitations.
Implement model re-authoring, operator decomposition, and graph transformations for backend-specific adaptations.
Convert and optimize models from PyTorch and ONNX for execution on AI accelerators.
Apply and validate quantization and calibration flows including mixed precision and accuracy-recovery techniques.
Measure and improve model accuracy, latency, throughput, memory consumption, and power efficiency.
Debug issues across model code, computational graphs, compilers, runtimes, and hardware layers.
Develop unit, integration, accuracy, performance, and on-device validation tests.
What we're looking for
Bachelor's degree in Computer Science, Engineering, or related field with 2+ years of experience in Hardware, Software, or Systems Engineering.
Master's degree in Computer Science, Engineering, or related field with 1+ year of experience in Hardware, Software, or Systems Engineering.
PhD in Computer Science, Engineering, or a related field.
1+ years of software development experience for Engineer level or 2+ years of software design and delivery experience for Senior Engineer level.
Proficiency in Python and/or C/C++ programming.
Strong understanding of software engineering fundamentals including data structures, algorithms, object-oriented design, debugging, and source control.
Foundational understanding of AI/ML concepts such as neural networks, deep learning, and model inference workflows.
Practical experience using agentic coding tools like Claude Code or OpenAI Codex to implement, test, and debug code.
Python
Kubernetes
AWS
Generative AI
Infrastructure as Code
LLM
System Design
Observability
Databases
Cloud-native Architecture
Root Cause Analysis
Automation
Python
Large Language Models (LLMs)
Agentic AI
RDF
OWL
SPARQL
Knowledge Graphs
Microsoft Fabric
Microsoft Azure
LangChain
Spark
SQL
ETL
ELT
CI/CD
MLOps
LLMOps
Microservices