Senior Engineer - Machine Learning

MaC VC; San Diego (CA); On-site; USD 141,000 - 211,000; Full time

Benefits offered by this job

Discretionary bonus program

RSU grants

Excellent benefits package

Job summary

Qualcomm Incorporated is seeking a Core ML Engineer to design, develop, and optimize machine learning systems powering AI platforms. You will focus on model development, inference optimization, and scalable ML infrastructure across enterprise systems.

The role requires strong software engineering fundamentals and deep ML expertise, with responsibilities spanning design, training workflows, and model serving at scale in an on-site San Diego environment.

Qualifications

• Bachelor's, Master's, or PhD in CS/Engineering or related field with relevant work experience.
• Strong programming skills in Python and at least one systems language (C++/Rust/Go).
• Experience with ML frameworks and model deployment is preferred. The role emphasizes production ML systems.

Responsibilities

• Design and implement production ML models and pipelines.
• Build scalable training, evaluation, and deployment workflows.
• Develop reusable ML components, libraries, and frameworks.

Skills

Python

Systems programming

Machine Learning

Distributed systems

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering

PhD in CS/Engineering

Tools

PyTorch

TensorFlow

Kubernetes

Docker

CI/CD

vLLM

ONNX

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 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.
• 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 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 disability‑[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).

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

• 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.