Q

Qualcomm

Designs mobile chips and licenses wireless patents

AI/ML Software Engineer - Gateway & Edge AI, Modem Software Engineering

Applied Machine LearningPosted on Nov 11
Full-timeSan Diego, CA, USAIn-person

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, AI/ML, or a related field is required; a Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field is also stated as a minimum qualification.
  • Strong programming skills in C/C++ and/or Python are required.
  • A strong understanding of software engineering fundamentals, data structures, algorithms, and system design is required.
  • An understanding of machine learning, deep learning, and Generative AI fundamentals is required.
  • Experience developing or integrating AI/ML models, large language models, or AI inference frameworks is required.
  • A good understanding of Linux systems development and debugging is required.
  • An understanding of AI performance characteristics, including latency, throughput, memory utilization, model accuracy, and compute requirements, is required.
  • Strong analytical and problem-solving skills and the ability to debug issues across software, AI models, and system layers are required.

Responsibilities

  • Design and develop AI and Generative AI features and use cases for gateway and edge products, translating real-world networking problems into production-ready AI solutions.
  • Develop AI-powered capabilities for network diagnostics, troubleshooting, optimization, security, automation, anomaly detection, and intelligent user experiences.
  • Integrate and optimize large language models, small language models, and machine-learning models for deployment on resource-constrained edge devices.
  • Develop on-device, cloud, and hybrid AI solutions, selecting the execution model based on latency, privacy, compute, memory, power, and connectivity requirements.
  • Build agentic AI and tool-calling capabilities that enable AI models to interact with device services, network telemetry, diagnostics, configuration, and other system functions.
  • Develop reusable AI inference, model-serving, and model-management capabilities for gateway applications.
  • Evaluate and optimize models for accuracy, latency, throughput, memory utilization, compute requirements, and power efficiency.
  • Apply AI optimization techniques such as quantization, fine-tuning, retrieval-augmented generation, prompt and context optimization, caching, and intelligent model selection and routing.
  • Prototype emerging AI use cases, evaluate their technical feasibility and product value, and transition successful concepts toward production.
  • Develop AI observability and diagnostics to measure model behavior, inference performance, resource utilization, and system reliability.
  • Collaborate with AI, networking, embedded software, cloud, application, and product teams to deliver production-quality AI features.
  • Evaluate emerging technologies in Generative AI, agentic AI, edge AI, multimodal AI, and AI runtimes, and identify opportunities to apply them to future gateway products.

Desired Qualifications

  • Experience deploying AI models on embedded, edge, Internet of Things, networking, or other resource-constrained devices is preferred.
  • Experience with large and small language models, model inference, quantization, fine-tuning, retrieval-augmented generation, prompt engineering, and context management is preferred.
  • Experience with agentic AI, function or tool calling, Model Context Protocol, or similar agent frameworks is preferred.
  • Familiarity with AI runtimes and hardware acceleration across central processing units, graphics processing units, and neural processing units is preferred.
  • Experience with model ecosystems and tooling such as PyTorch, ONNX, Hugging Face, GGUF, or equivalent frameworks is preferred.
  • An understanding of networking, broadband gateways, Wi-Fi, telemetry, diagnostics, or network management is preferred.
  • Experience profiling and optimizing AI workloads for latency, memory, compute, and power constraints is preferred.
  • Experience taking AI capabilities from prototype through productization and production deployment is preferred.

About the Company

Qualcomm

Designs mobile chips and licenses wireless patents

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Diego, CA
Founded
1985

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