Senior Engineer - Machine Learning

QUALCOMM, Inc.; San Diego (CA); On-site; USD 141,000 - 211,000; Full time

Job summary

Qualcomm Incorporated in San Diego, CA seeks a Core ML Engineer to design, develop, and optimize machine learning systems powering next-gen AI platforms and applications. You will build scalable ML pipelines, optimize inference, and deploy models across APIs and microservices in production environments.

The ideal candidate combines strong software engineering with deep ML expertise, capable of delivering robust, high-performance systems at scale in a collaborative, hardware-aware setting.

Qualifications

• Bachelor's degree in CS/EE or related field with 2+ years in hardware/ software/ systems engineering.
• Master's degree with 1+ year experience or PhD in related field.

Responsibilities

• Design and implement production ML models and pipelines.
• Optimize model inference for low latency, high throughput, and cost.
• Integrate ML/LLM models into APIs, microservices and apps.
• Build scalable model-serving infrastructure and data pipelines.

Skills

Python

C++

ML fundamentals

Transformer architectures/LLMs

Model evaluation & debugging

Education

Bachelor's degree with 2+ years exp

Master's degree with 1+ year exp

PhD in relevant field

Tools

PyTorch

TensorFlow

ONNX

vLLM

OpenSearch / Qdrant

Docker

Kubernetes

Job description

Company:Qualcomm IncorporatedJob Area:Engineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:We are seeking a highly skilled Core ML Engineer to design, develop, and optimize machine learning systems that power next-generation AI platforms and applications. This role focuses on model development, inference optimization, and scalable ML infrastructure, enabling production-grade AI capabilities across enterprise systems.The ideal candidate combines strong software engineering fundamentals with deep ML expertise, and thrives in building robust, high-performance systems at scale.Key ResponsibilitiesCore ML System DevelopmentDesign and implement machine learning models and pipelines for production useBuild scalable training evaluation deployment workflowsDevelop reusable ML components, libraries, and frameworksInference & Performance OptimizationOptimize model inference for latency, throughput, and costImplement advanced techniques such as caching, quantization, batching, and routingBenchmark and profile models across diverse workloads and hardware environmentsModel Integration & DeploymentIntegrate ML/LLM models into APIs, microservices, and applicationsBuild 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 validationImprove data quality and model reliability through systematic evaluationCross-functional CollaborationPartner with product, platform, and hardware teams to deliver end-to-end ML solutionsParticipate in design reviews and contribute to system architecture decisionsMinimum Qualifications:• Bachelor'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.ORMaster'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.ORPhD in Computer Science, Engineering, Information Systems, or related field.Preferred QualificationsStrong programming skills in Python and at least one systems language (C++/Rust/Go)Solid understanding of:Machine learning fundamentals (supervised, unsupervised, deep learning)Transformer architectures / LLMsModel evaluation and debuggingExperience with:ML frameworks (PyTorch, TensorFlow)Model deployment and serving systemsBuilding scalable software and APIsExperience with:Large Language Models (LLMs), multimodal models, or generative AIRetrieval systems and RAG pipelinesDistributed computing and GPU/accelerator environments including model serving and efficient cache/state management (e.g. KV cache, embeddings) across disaggregated systemsKubernetes, Docker, and CI/CD pipelinesAgentic and multi-step AI workflows, tool integration, orchestration, and multi-component pipelinesKnowledge of:Model 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 strategiesThis 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 [e-mail] 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).To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.EEO Employer: 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.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.Pay range and Other Compensation & Benefits :$140,800.00 - $211,200.00The 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. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link .If you would like more information about this role, please contact Qualcomm Careers .