Staff Engineer, Application Engineering; AI
Job in
Santa Clara, Santa Clara County, California, 95053, USA
Listed on 2026-02-17
Listing for:
Qualcomm
Full Time
position Listed on 2026-02-17
Job specializations:
-
Software Development
AI Engineer, Software Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Company:
Qualcomm Atheros, Inc.
Job Area:Engineering Group, Engineering Group >
Software Applications Engineering
General
Summary:
As a Staff Application Software Engineer in the WIN Customer Engineering team, you will lead the integration of state-of-the-art AI/ML capabilities into Qualcomm’s next-generation Wi-Fi 7 and Wi-Fi 8 Access Point platforms. You will bridge the gap between advanced AI research and commercial deployment, helping Tier-1 customers run optimized CNNs and LLMs directly on the edge device (AP/Router).
This role requires a unique blend of Machine Learning expertise (quantization, model optimization) and Embedded Systems knowledge (DDR profiling, Linux kernel) to ensure AI applications operate efficiently.
Key Responsibilities- Model Optimization:
Lead the optimization of AI models (CNNs, Transformers, LLMs) for deployment on resource-constrained embedded targets. Utilize Quantization techniques (INT8/INT4) and pruning to fit models within limited memory (DDR) and compute budgets. - Hardware Acceleration:
Offload inference workloads to the Hexagon NPU (NSP) and DSP to maximize performance per watt, ensuring minimal impact on the host CPU. - Debug & Profiling: perform deep-dive debugging of accuracy loss during quantization and runtime inference failures.
- Network Agents:
Develop "Agentic" workflows where local LLMs (e.g., Llama 3, Phi-3) analyze network telemetry to autonomously optimize Wi-Fi performance (e.g., "Gaming Mode" QoS tuning, Mesh steering) or assist with troubleshooting. - Edge Inference:
Implement pipelines for on-device Generative AI and Multi-modal models (Vision + Text) to enable smart sensing and security features on the Gateway.
- Resource Management:
Conduct rigorous CPU and DDR profiling to ensure AI workloads do not starve the networking stack (packet processing latency, throughput). Tune system memory interaction between the NPU, CPU, and Wi-Fi subsystems. - Integration:
Integrate AI inference engines (e.g., TFLite, ONNX Runtime, Qualcomm AI Stack) into the Open Wrt/Linux based SDK.
- Technical Leadership:
Serve as the AI subject matter expert for customers, guiding them on model selection, training pipelines, and deployment strategies for Qualcomm platforms. - Cloud Hybridization:
Architect solutions that balance edge processing with cloud-based model updates and scalability.
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Applications Engineering, Software Development experience, or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering, Software Development experience, or related work experience. - 2+ years of experience with Programming Language such as C, C++, Java, Python, etc.
- 1+ year of experience with debugging techniques.
- Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field.
- Experience:
5+ years of software engineering experience with a strong focus on Embedded AI/ML. - AI/ML Expertise:
Deep proficiency in PyTorch or Tensor Flow. Hands-on experience with CNNs (Object Detection, Classification) and LLMs (Transformers). - Model Optimization:
Expert knowledge of Model Quantization (Post-Training Quantization, QAT), model compression, and debugging accuracy issues. - Systems Programming:
Strong coding skills in C/C++ and Python. Experience with Linux user-space development, multi-threading, and memory management. - Performance Profiling:
Proficiency with profiling tools (e.g., perf, eBPF, hardware counters) to analyze DDR bandwidth, cache misses, and CPU load. - Soft Skills:
Excellent problem-solving abilities and communication skills to articulate complex AI concepts to networking engineers and customers.
EEO…
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