distributed-computing jobs in San Diego

Lead Qualcomm's next-generation AI accelerator platform as senior engineering director, defining software vision, architecture, and roadmap while managing multiple engineering organizations spanning system software, device drivers, AI runtimes, compilers, ML frameworks, and platform SDKs. Partner with hardware teams on co-design, drive software readiness across chip development milestones, and establish performance/power/reliability goals.…See more Requires 9+ years software engineering experience (or PhD + 8 years), 4+ years with C/C++/Java/Python, and demonstrated expertise in AI/ML stacks, compiler technologies, runtime systems, or high-performance computing.

Sr. Director leading Qualcomm's next-generation AI accelerator platform software strategy, architecture, and delivery.…See more Manages multiple engineering organizations spanning system software, firmware, device drivers, AI runtimes, compilers, ML frameworks, SDKs, and validation. Defines performance and reliability goals, drives cross-functional hardware-software co-design, and partners with customers and hyperscalers. Requires 15+ years software engineering experience with 8+ years leading large, globally distributed teams; deep expertise in AI/ML stacks, compilers, runtime systems, or heterogeneous computing architectures.

Design, develop, and optimize machine learning systems and models for production AI platforms, with focus on inference optimization, scalable ML infrastructure, and deployment. Responsibilities include building ML pipelines, optimizing model inference across hardware environments, integrating LLMs and models into APIs and microservices, designing data pipelines for ingestion and feature engineering, and collaborating cross-functionally on end-to-end ML solutions.…See more Requires strong software engineering fundamentals combined with deep ML expertise, proficiency in Python and at least one systems language (C++, Rust, or Go), and solid understanding of ML frameworks, transformer architectures, and model deployment systems.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs.…See more Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.

Lead a specialized team of software engineers developing innovative Pixel sensor experiences at the intersection of hardware, software, and AI. You will drive the design and implementation of real-time embedded systems that process sensor signals efficiently while applying machine-learning and signal-processing algorithms in a power-optimized manner.…See more Required: 8 years software development experience, 5 years in computer vision or signal processing, 5 years leading ML design and infrastructure optimization, and 3 years technical leadership. This role demands deep expertise in embedded software, AI/ML algorithms, sensor fusion, and the ability to independently architect systems while managing a team.