Data Center AI Software Senior Customer Engineer

Company:

Qualcomm China

Job Area:

General Summary:

Role Overview

The Data Center Customer Engineering team is seeking a Cloud AI Software Senior Engineer to support deployment and customer enablement of AI and generative AI workloads on Qualcomm Cloud AI inference accelerators. This role is designed for a strong software engineer with AI/ML exposure who can bring up customer workloads, integrate software components, automate validation, investigate functional and performance issues, and collaborate effectively with internal engineering teams. Deep expertise in LLM kernel optimization, distributed training, or rack-scale performance architecture is helpful but not required.

Key Responsibilities

· Deploy, integrate, and validate AI/ML and LLM inference workloads on Qualcomm Cloud AI accelerator platforms.

· Support customer model onboarding, environment setup, functional validation, basic performance benchmarking, and issue reproduction.

· Work with AI frameworks, model conversion/deployment flows, runtime APIs, and accelerator software stacks to enable customer use cases.

· Debug software issues across applications, frameworks, runtime, drivers, operating system, and platform interfaces; collect logs and traces and drive clear issue reports.

· Perform basic LLM performance analysis using metrics such as latency, throughput, tokens/second, Time to First Token (TTFT), and resource utilization; escalate deep optimization topics to specialist teams when appropriate.

· Create and maintain Python/Bash automation for model deployment, regression tests, benchmark execution, log collection, and result analysis.

· Support single-server and basic multi-accelerator/multi-node validation; develop working knowledge of Scale-Up/Scale-Out and collective communication concepts such as AllReduce and AllGather.

· Collaborate with model, runtime, compiler, driver, firmware, platform, and infrastructure teams to reproduce issues, identify ownership, and track resolution.

· Assist customer PoCs and production-readiness activities, including release validation, upgrade testing, configuration verification, and technical documentation.

· Document setup procedures, known issues, troubleshooting guides, benchmark results, and reusable customer enablement best practices.

Required Qualifications

· Master’s degree in Computer Science, Electrical/Computer Engineering, Software Engineering, or a related technical discipline, or equivalent practical experience.

· Solid software development and debugging skills in Python and/or C/C++, plus practical Bash/Linux command-line experience.

· Good understanding of Linux software environments, processes, memory, networking basics, logs, packages, containers, and system troubleshooting.

· Practical exposure to AI/ML inference and at least one framework such as PyTorch, ONNX Runtime, Hugging Face Transformers, or an equivalent framework/runtime.

· Basic understanding of Transformer and LLM concepts, including tokens, attention, context length, KV cache, prefill/decode, and common inference performance metrics.

· Experience with software integration, validation, test automation, issue reproduction, and root-cause analysis across multiple software components.

· Ability to analyze technical problems methodically and communicate findings clearly to internal engineering teams and customers.

· Comfort working directly with customers or partners in evaluation,

integration, or technical support environments.

Preferred Qualifications

· Experience deploying LLMs or generative-AI applications using Hugging Face, vLLM, SGLang, DeepSpeed, or similar software stacks.

· Exposure to model optimization techniques such as quantization, batching, KV-cache management, or graph/runtime optimization.

· Familiarity with Docker and Kubernetes and common datacenter deployment workflows.

· Basic knowledge of multi-GPU/multi-accelerator systems, PCIe/network topology, RDMA/RoCE/InfiniBand, or collective communication.

· Experience with performance profiling, benchmark automation, CI/CD, telemetry, or regression analysis.

· Experience supporting accelerator, GPU, NPU, server, cloud, or other Linux-based compute platforms.

Minimum Qualifications:

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Applications Engineering, Software Development experience, or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field.

• 1+ year of any combination of academic and/or work experience with Programming Language such as C, C++, Java, Python, etc.

• 1+ year of any combination of academic and/or work experience with debugging techniques.

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