Engineer, Principal

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Edge AI Appliance Engineering Lead

Job Overview

Qualcomm is building next-generation Edge AI Appliance platforms that bring high-performance, power-efficient AI inference to enterprise and edge environments.

We are seeking an experienced engineering leader to drive the architecture, development, integration, and commercialization of Qualcomm-based Edge AI Appliances. This role spans the complete product lifecycle, from platform architecture and hardware/software co-design through AI workload enablement, system optimization, production readiness, and customer deployment.

The ideal candidate combines deep expertise in AI/ML systems, platform software, heterogeneous computing, and performance engineering with a proven ability to build and lead high-performing engineering teams.

Key Responsibilities

• Own the end-to-end architecture and engineering execution of Qualcomm Edge AI Appliance platforms.
• Lead hardware/software co-design across compute, AI acceleration, memory, storage, networking, security, and system software.
• Drive enablement and optimization of Generative AI, LLM, multimodal, vision, speech, and traditional ML workloads.
• Lead integration of AI frameworks, inference runtimes, compilers, and model-serving technologies such as PyTorch, ONNX, vLLM, Triton, ExecuTorch, and MLIR.
• Optimize end-to-end system performance across latency, throughput, memory, power, thermal efficiency, and data movement.
• Drive appliance platform capabilities including Linux, containers, system services, telemetry, observability, security, software updates, and lifecycle management.
• Architect scalable solutions spanning single-appliance through distributed multi-node Edge AI deployments.
• Establish robust software integration, CI/CD, validation, release, and production-readiness practices.
• Partner with silicon, system architecture, AI software, security, product, and customer engineering teams to translate customer requirements into scalable platform capabilities.
• Build and lead a high-performing multidisciplinary engineering organization while developing strong technical and architectural leadership across the team.

Desired Skills & Experience

• Strong experience building Edge, AI Infrastructure, Data Center, embedded, or appliance-class platforms.
• Deep understanding of AI inference architectures, heterogeneous computing, and hardware/software co-optimization.
• Experience with PyTorch and modern AI inference/runtime ecosystems.
• Knowledge of LLM inference, graph compilers, MLIR, operator optimization, scheduling, and accelerator runtimes.
• Strong understanding of Linux system software, networking, containers, security, and platform manageability.
• Excellent C/C++ and Python skills with experience in profiling and performance optimization.
• Experience scaling workloads across multiple accelerators, SoCs, or distributed systems.
• Proven track record taking complex hardware/software platforms from architecture through commercial deployment.
• Strong communication and cross-functional leadership skills.

Qualifications

• Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, AI/ML, or a related field.
• 15+ years of software, systems, AI infrastructure, or platform engineering experience.
• Significant experience leading technically complex engineering teams and programs.
• Demonstrated ability to operate across silicon, systems, software, AI, product, and customer organizations.

Minimum Qualifications:

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