5 days ago
San Diego, CA, USAMid Level
H1B sponsor
Base Salary
$109k - $164k/yr
Responsibilities
- Design and develop AI and Generative AI features for gateway and edge products.
- Create AI-powered capabilities for network diagnostics, troubleshooting, optimization, security, automation, anomaly detection, and intelligent user experiences.
- Integrate and optimize LLMs, SLMs, and ML models for resource-constrained edge devices.
- Develop on-device, cloud, and hybrid AI solutions based on latency, privacy, compute, memory, power, and connectivity requirements.
- Build agentic AI and tool-calling capabilities that interact with device services, telemetry, diagnostics, configuration, and system functions.
- Develop reusable AI inference, model-serving, and model-management capabilities for gateway applications.
- Evaluate and optimize model accuracy, latency, throughput, memory utilization, compute requirements, and power efficiency.
- Apply quantization, fine-tuning, RAG, prompt/context optimization, caching, and model selection or routing techniques.
- Prototype emerging AI use cases and transition successful concepts into production.
- Develop AI observability and diagnostics for model behavior, inference performance, resource utilization, and system reliability.
- Collaborate with AI, networking, embedded software, cloud, application, and product teams.
- Evaluate emerging Generative AI, agentic AI, edge AI, multimodal AI, and AI runtime technologies.
Requirements
- Bachelor's or master's degree in Computer Science, Computer Engineering, Electrical Engineering, AI/ML, or a related field.
- Strong programming skills in C/C++ and/or Python.
- Strong understanding of software engineering fundamentals, data structures, algorithms, and system design.
- Understanding of machine learning, deep learning, and Generative AI fundamentals.
- Experience developing or integrating AI/ML models, LLMs, or AI inference frameworks.
- Good understanding of Linux systems development and debugging.
- Understanding of AI performance characteristics including latency, throughput, memory utilization, model accuracy, and compute requirements.
- Strong analytical and problem-solving skills, including debugging across software, AI models, and system layers.
- Preferred experience deploying AI models on embedded, edge, IoT, networking, or other resource-constrained devices.
- Preferred experience with LLMs/SLMs, model inference, quantization, fine-tuning, RAG, prompt engineering, context management, agentic AI, function/tool calling, MCP, or similar agent frameworks.
- Preferred familiarity with AI runtimes and hardware acceleration across CPU, GPU, and NPU.
- Preferred experience with PyTorch, ONNX, Hugging Face, GGUF, or equivalent model ecosystems and tooling.
- Preferred understanding of networking, broadband gateways, Wi-Fi, telemetry, diagnostics, or network management.
- Preferred experience profiling and optimizing AI workloads and taking AI capabilities from prototype through production deployment.
Benefits
- Annual discretionary bonus program and potential annual RSU grants are available in addition to base pay.
- Competitive benefits package supporting employees at work, at home, and at play.
- The position is posted with a broad pay scale for the applicable location; the recruiter can provide further benefits details.
- Qualcomm provides reasonable accommodations during the application and hiring process.
Categories
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.