Senior Engineer - Machine Learning

• Partner with product, platform, and hardware teams to deliver end-to-end ML solutions
• Participate in design reviews and contribute to system architecture decisions

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

• ML frameworks (PyTorch, TensorFlow)
• Model deployment and serving systems
• Building scalable software and APIs

• 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

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Pay range and Other Compensation & Benefits :

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 .

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