Senior Engineer - Machine Learning

Key Responsibilities: Core ML System DevelopmentDesign and implement machine learning models and pipelines for production use Build scalable training → evaluation → deployment workflows Develop reusable ML components, libraries, and frameworksInference & Performance OptimizationOptimize model inference for latency, throughput, and cost Implement advanced techniques such as caching, quantization, batching, and routing Benchmark and profile models across diverse workloads and hardware environmentsModel Integration & DeploymentIntegrate ML/LLM models into APIs, microservices, and applications Build and maintain model‑serving infrastructure (e.g., vLLM, ONNX, custom runtimes) Collaborate with platform and infrastructure teams for scalable deploymentData & Pipeline EngineeringDesign data pipelines for ingestion, preprocessing, feature engineering, and validation Improve data quality and model reliability through systematic evaluationCross-functional CollaborationPartner with product, platform, and hardware teams to deliver end‑to‑end ML solutions Participate in design reviews and contribute to system architecture decisionsMinimum QualificationsBachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. PhD in Computer Science, Engineering, Information Systems, or related field.

Preferred Qualifications: Strong programming skills in Python and at least one systems language (C++/Rust/Go) Solid Understanding OfMachine learning fundamentals (supervised, unsupervised, deep learning) Transformer architectures / LLMs Model evaluation and debugging Experience WithML frameworks (PyTorch, TensorFlow) Model deployment and serving systems Building scalable software and APIs Experience WithLarge Language Models (LLMs), multimodal models, or generative AI Retrieval systems and RAG pipelines Distributed computing and GPU/accelerator environments including model serving and efficient cache/state management (e.g. KV cache, embeddings) across disaggregated systems Kubernetes, Docker, and CI/CD pipelines Agentic and multi‑step AI workflows, tool integration, orchestration, and multi‑component pipelines Knowledge OfModel optimization techniques (quantization, distillation, caching) Vector databases and search systems (OpenSearch, Qdrant, etc.) Cost‑aware system design – model routing (small vs. large models), dynamic batching, and caching strategies This is an office-based position located in San Diego, CA and is expected to comply with the company's onsite work policy. Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e‑mail disability‑accomodations@qualcomm.com or call Qualcomm's toll‑free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Pay Range and Other Compensation & Benefits$140,800.00 - $211,200.00 The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales‑incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. If you would like more information about this role, please contact Qualcomm Careers.