onnx jobs in San Diego

Design, implement, and optimize video processing and computer vision algorithms for mobile and embedded platforms at scale, from concept through production deployment. Profile and optimize algorithm performance across memory, compute, power, and bandwidth constraints on SoCs with embedded accelerators.…See more Lead system and algorithm-level architecture, collaborate with cross-functional hardware and software teams, and provide technical mentorship to engineers across experience levels.

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.

As a Senior Software Engineer focused on AI Tools, you will reauthor and optimize generative AI models (LLMs like Llama, Phi, Qwen, and multimodal models) for efficient execution on Qualcomm's on-device hardware. You'll translate hardware constraints into model-level transformations that preserve accuracy while enabling edge deployment, integrate inference acceleration techniques, and collaborate with compiler and quantization teams to move research prototypes into production.…See more The role requires deep implementation-level knowledge of generative AI architectures, strong Python proficiency in large typed codebases, and hands-on experience optimizing inference for resource-constrained environments.

Own CI, build, and release infrastructure for AI software products (ONNX Runtime, ExecuTorch, TFLite/LiteRT delegates) across Linux, Windows, and Android. Design and evolve multi-platform CI pipelines, implement HIL and on-device automated testing for Snapdragon SoC validation, and drive end-to-end release pipelines with versioning, artifact packaging, and distribution.…See more Define automated quality gates including regression benchmarks and performance thresholds. Requires 8+ years of software/DevOps/release engineering experience (or 6+ with a Master's), expert Python and Bash scripting, deep CI/CD platform expertise (Jenkins, GitLab CI, GitHub Actions, TeamCity), and hands-on experience integrating AI coding agents into workflows.

Qualcomm is seeking an AI Performance Engineer to optimize and deploy machine learning models for inference acceleration on cloud AI hardware. The role involves converting and optimizing language models, vision models, and diffusion models using PyTorch and ONNX, analyzing performance bottlenecks, and designing efficient kernels in Triton.…See more You will collaborate with compiler, firmware, and platform teams to map next-generation AI workloads onto hardware, working across the full product lifecycle from research to commercial deployment. The position requires deep expertise in transformer architectures, inference optimization techniques, computer architecture, ML accelerators, and distributed systems.

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.