Performance & Modeling Engineer - Software Engineering

Company:

Job Area:

Engineering Group, Engineering Group > Software Engineering

General Summary:

Qualcomm Cloud AI is seeking an experienced Performance & Modeling Engineer to deploy, enable, benchmark, and optimize state-of-the-art AI models on Qualcomm Cloud AI platforms. In this role, you will leverage Qualcomm Cloud AI toolchains to rapidly bring up industry-leading AI workloads, analyze performance bottlenecks, drive model accuracy and performance optimization, and deliver best-in-class inference efficiency for cloud-scale AI deployments.

Key Responsibilities

• Deploy and optimize LLM, MoE, and multimodal models on Qualcomm Cloud AI platforms.
• Analyze and improve model accuracy, latency, throughput, memory utilization, and scalability.
• Drive graph-level, framework-level, and system-level optimizations.
• Benchmark AI workloads and identify performance bottlenecks across the software and hardware stack.
• Work closely with compiler, runtime, kernel, and architecture teams to improve model enablement and performance.
• Support customer deployment, bring-up, performance tuning, and production readiness.

Required Qualifications

• Master's degree or above in Computer Science, Artificial Intelligence, Mathematics, Electrical Engineering, or related fields.
• Good verbal and written English communication skills to effectively collaborate across global teams.
• Strong experience with Python, C++, and Linux development environments.
• 5+ years of experience in Cloud AI, LLM deployment, or AI infrastructure.
• Deep understanding of Transformer architectures, LLMs, and MoE models.
• Strong experience in graph optimization and model compilation workflows.
• Strong experience in model accuracy and performance optimization.
• Strong experience with one or more AI frameworks, including PyTorch, ONNX, TensorFlow, or JAX.
• Experience with AI serving frameworks such as vLLM, SGLang, TGI, TensorRT-LLM, or LMDeploy.

Preferred Qualifications

• Familiarity with AI accelerator platforms and large-scale inference systems.
• Experience with Quantization, KV-Cache optimization, speculative decoding, continuous batching, Prefix Caching, Parallelism Strategies and distributed inference.
• Experience with performance modeling and analysis methodologies, including Roofline analysis, bottleneck identification across software and hardware stacks.
• Familiarity with open-source inference frameworks such as llama.cpp, Ollama, or MLC-LLM.
• Experience with Kubernetes, Docker, and cloud-native AI infrastructure.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

• 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

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If you would like more information about this role, please contact Qualcomm Careers.