Company:
Qualcomm Incorporated
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General 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 Responsibilities
Core ML System Development
- Design and implement machine learning models and pipelines for production use
- Build scalable training → evaluation → deployment workflows
- Develop reusable ML components, libraries, and frameworks
Inference & Performance Optimization
- Optimize 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 environments
Model Integration & Deployment
- Integrate 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 deployment
Data & Pipeline Engineering
- Design data pipelines for ingestion, preprocessing, feature engineering, and validation
- Improve data quality and model reliability through systematic evaluation
Cross-functional Collaboration
- Partner with product, platform, and hardware teams to deliver end-to-end ML solutions
- Participate in design reviews and contribute to system architecture decisions
Minimum 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.
OR
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.
OR
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 of:
- Machine learning fundamentals (supervised, unsupervised, deep learning)
- Transformer architectures / LLMs
- Model evaluation and debugging
Experience with:
- ML frameworks (PyTorch, TensorFlow)
- Model deployment and serving systems
- Building scalable software and APIs
Experience with:
- Large 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 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 strategies
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 [email protected] 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 - $211,200.00
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. 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.
