Senior Engineer - Machine Learning

Qualcomm Incorporated; 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, optimize, and scale machine learning systems powering next-generation AI platforms. You will own model development, inference performance, and ML infrastructure for production workloads.

You bring strong software fundamentals and ML expertise to build robust systems, integrate models into APIs, and collaborate with platform and hardware teams to deliver end-to-end ML solutions at scale.

Qualifications

• Strong programming skills in Python and at least one systems language.
• Solid foundation in ML fundamentals, transformers, and model debugging.
• Experience with ML frameworks and scalable deployment.

Responsibilities

• Core ML system development and production-grade model pipelines.
• Inference optimization for latency, throughput, and cost.
• Develop reusable ML components, libraries, and APIs.
• Collaborate with platform and hardware teams for scalable deployment.

Skills

Python

C++/Rust/Go

ML fundamentals

Transformer architectures

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Master's degree in Computer Science, Engineering, Information Systems, or related field

PhD in Computer Science, Engineering, Information Systems, or related field

Tools

PyTorch

TensorFlow

Model deployment and serving systems

Kubernetes

CI/CD pipelines

Job description

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 evaluationCross-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

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 [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).

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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 .