AI Performance Engineer (Cloud AI Engineering), Sr | Staff | Sr. Staff

Company: Qualcomm Technologies, Inc. Job Area: Engineering Group > Machine Learning Engineering General Summary: Qualcomm is utilizing its traditional strengths in digital wireless technologies to play a central role in the evolution of Cloud AI. The Qualcomm Cloud AI team is developing hardware and software solutions for Inference Acceleration. Responsibilities Convert, optimize and deploy models for efficient inference using PyTorch and ONNX. Work at the forefront of GenAI by understanding advanced algorithms (e.g., attention mechanisms, MoEs) and numerics to identify new optimization opportunities. Analyze performance and optimize LLM, VLM, and diffusion models for inference, scaling performance for throughput and latency constraints. Map next-generation AI workloads on top of current and future hardware designs. Collaborate with customers and internal compiler, firmware, and platform teams to drive solutions. Analyze complex performance or stability issues to determine root causes. Create engineering solutions that deliver continuous insights into performance of AI workloads, guiding improvements over time. Design and implement high-level kernels (e.g., in Triton) focused on generating efficient, low-level code. Qualifications Hands‑on experience building and optimizing language models, notably in PyTorch and ONNX, preferably in production‑grade environments. Deep understanding of transformer architectures, attention mechanisms, and performance trade‑offs. Experience with workload‑mapping strategies exhibiting sharding or various parallelisms. Strong Python programming skills. Proactive learning about the latest inference optimization techniques. Understanding of computer architecture, ML accelerators, in‑memory processing, and distributed systems. Strong communication, problem‑solving skills, and ability to work effectively in a fast‑paced, collaborative environment. MS in Computer Science, Machine Learning, Computer Engineering, or Electrical Engineering. Bonus Skills Background in neural network operators and mathematical operations, including linear algebra and math libraries. Understanding of machine learning compilers. Experience in converging accuracy and its evaluation methods. Knowledge of torch.compile or torchDynamo. PhD in Computer Science, Computer Engineering, or Machine Learning. Minimum Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of hardware, software, or systems engineering experience. Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of hardware, software, or systems engineering experience. PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of hardware, software, or systems engineering experience. Compensation & Benefits Pay range: $178,400.00 – $267,600.00. Competitive annual discretionary bonus program and annual RSU grants. Highly competitive benefits package. Qualcomm is an equal opportunity employer. If you are an individual with a disability and need accommodation during the application/hiring process, Qualcomm is committed to providing an accessible process and will provide reasonable accommodations to support participation. #J-18808-Ljbffr Qualcomm