Senior Engineer - Machine Learning

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  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.

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 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 / LLMsModel evaluation and debugging

Experience with :

ML frameworks (PyTorch, Tensor Flow)
Model deployment and serving systems

Building scalable software and APIsExperience 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 (Open Search, Qdrant, etc.)Cost-aware system design – model routing (small vs. large models), dynamic batching, and caching strategies

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