pytorch jobs in San Diego

Build and optimize scalable LLM inference platforms at Qualcomm's Cloud AI team, implementing advanced serving techniques like KV-cache management, speculative algorithms, and model optimization. Contribute to production serving frameworks (vLLM, SGLang, Triton, TGI) and work with customers on deployment solutions.…See more Collaborate with compiler, firmware, and platform teams to drive efficient serving through autoscaling, load balancing, and routing. Requires deep understanding of transformer architectures, strong PyTorch and Python skills, computer architecture knowledge, and hands-on experience profiling and optimizing deep learning workloads.

Senior Embedded Software Engineer role at Qualcomm's Data Center Business Unit focused on designing and developing software/firmware for cloud edge and data center ML acceleration on high-performance silicon. The role requires deep expertise in embedded systems including board support packages, device drivers, RTOS, secure boot, TrustZone, and low-speed peripherals (I2C/SPI/UART), combined with proficiency in C/C++ development, debugging with JTAG/SWD, and embedded Linux.…See more Responsibilities include ML acceleration, process-in-memory optimization, memory management, virtualization, and collaboration with cross-functional teams. Ideal candidate has 2+ years of low-level C programming and background in SoC architecture, DMA, PCIe, and multi-threaded programming.

As a Machine Learning Application Developer, you will develop and optimize neural rendering applications and ML software for efficient AI execution on Samsung's mobile GPUs. Working with hardware and software teams, you'll optimize performance and resource utilization by developing API-level software, ML operator implementations (GEMM, convolution, activations), and conducting low-level performance analysis.…See more The role requires strong C/C++/Python skills, proficiency with Vulkan/OpenGL/OpenCL, hands-on neural rendering experience, and deep understanding of GPU architecture and performance optimization techniques.

Senior Machine Learning Engineer responsible for architecting, designing, developing, and deploying on-device AI prototype software for edge computing applications. The role requires expert-level proficiency in C++ and Python, deep knowledge of ML frameworks like PyTorch, and hands-on experience with low-level system debugging, performance tuning, and native inference driver development.…See more You will work in a multi-disciplinary research team advancing generative AI technology for the edge, including model fine-tuning, hardware acceleration, model quantization, and edge inference. A strong theoretical background in deep learning combined with embedded software development experience and modern software engineering best practices is essential.

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.

Senior Engineer, Machine Learning at Element Biosciences will design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net) for biological image analysis and deploy them to production on AWS or imaging instruments. Responsibilities include building end-to-end ML pipelines from data ingestion through inference, applying advanced image processing and computer vision techniques to multimodal biological images, and analyzing single-cell and multiomic data.…See more The role requires 5–7 years of experience with a Master's degree (or 0–3 years with a PhD) and hands-on proficiency in PyTorch, Python, and cloud deployment, with strong preference for experience in biomedical image modalities.

Staff-level embedded software engineer responsible for designing and developing AI, GenAI, and multimedia SDKs/frameworks for IoT edge devices (drones, cameras, AI boxes, appliances). The role requires architecting high-performance inference pipelines, multi-stream AI processing, and GStreamer-based plugins for Qualcomm hardware platforms.…See more Must have 5+ years of C/C++ experience in embedded systems, strong knowledge of AI inference frameworks (PyTorch, TensorFlow, ONNX Runtime, LiteRT), GenAI orchestration tools (LangChain, LlamaIndex), and multimedia/HAL integration across Android, Tizen, and Linux. Ownership spans architecture, design, implementation, and deployment of production-quality SDK components.

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.

Lead research projects in AI/ML across areas including decision-focused AI, probabilistic modeling, causal inference, agentic systems, neuro-symbolic AI, and LLM-based reasoning. Define technical direction, mentor junior researchers, and translate research innovations into Intuit's products.…See more Requires a PhD, 8+ years of post-PhD research experience with top-tier publications, and deep expertise in one or more focus areas. Proficiency in Python, PyTorch, or TensorFlow, and strong fundamentals in deep learning, optimization, and statistical machine learning are essential.

Principal Machine Learning Engineer at AppFolio to architect and lead mission-critical AI systems across the Realm-X property management platform. You'll design advanced AI agentic systems combining reasoning, planning, and execution; establish ML platform primitives for end-to-end production workflows; and drive the transition toward autonomous property management using LLMs, fine-tuning, and reinforcement learning.…See more Requires 10+ years building software systems with deep expertise in traditional ML, deep learning, generative AI, LLM post-training (SFT, RLHF, DPO, RL), and production ML at scale—plus a Master's or Ph.D. in Computer Science or related field.

Lead the design and implementation of computer vision features and on-device prototyping using Snapdragon Vision API. Support engineering teams in building, integrating, and deploying CV APIs for commercial products across mobile, autonomous vehicles, IoT, and AR/VR platforms.…See more Develop technical documentation and sample materials showcasing CV capabilities to end-application developers. Requires 3–5 years of hands-on CV application development, strong understanding of CV algorithms and deep-learning pipelines, and proficiency in C/C++ and Python for rapid on-device prototyping.

Build full-stack applications incorporating AI, data analytics, cloud technologies, and DevOps for mission-focused projects. You will develop and deploy features using Python, Django, React, APIs, and big data applications while working across the full technology stack.…See more The role requires 2+ years of professional software development experience with proficiency in Python-based web frameworks, front-end technologies (React, JavaScript, TypeScript), databases (PostgreSQL, MySQL, NoSQL), and basic CI/CD and Git knowledge. You'll collaborate in an Agile environment supporting diverse applications in maintenance planning, maritime analysis, and extreme weather assessment.

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.

Join Qualcomm AI Research as a Machine Learning Engineer to architect, design, develop, and deploy on-device AI prototype software for edge devices. You will work with a multi-disciplinary team using cutting-edge AI frameworks, focusing on model fine-tuning, quantization, and edge inference.…See more Strong Python, deep learning frameworks (PyTorch), object-oriented design, and software engineering best practices are required. Preferred qualifications include generative AI knowledge, neural network optimization, NPU/ML accelerator experience, Android programming, C/C++, and embedded software skills.

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, implement, and verify machine learning software for embedded systems running on ARM processors, DSPs, and GPUs in mobile, edge, automotive, and IoT products. Develop optimized ML kernels, compilers, and tools; optimize ML frameworks like TensorFlow and PyTorch for efficient hardware execution.…See more Perform integration, testing, and performance optimization of embedded software subsystems. Collaborate with hardware teams on joint design and development, coordinate cross-team dependencies, and contribute to design reviews.

Qualcomm seeks an experienced Staff Product Manager to define and drive the Linux platform roadmap across Snapdragon-based AI PCs, Edge AI systems, and enterprise computing solutions. The role spans product strategy, Linux distribution enablement, upstream kernel and driver strategy, and AI developer platform support.…See more You will gather customer and ecosystem requirements, create product roadmaps, collaborate with OEMs, ISVs, Linux distribution partners, and open-source communities to deliver optimized Linux experiences on Snapdragon platforms. Success requires translating market needs into platform requirements, managing cross-functional alignment across hardware, firmware, kernel, and AI software layers.

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.

As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions.…See more You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace.…See more Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

Design and optimize video analysis and quality assessment algorithms for next-generation video codec hardware accelerators (FPGA/ASIC). Implement C-models and firmware for advanced video encoding, collaborating across algorithm, architecture, software, and hardware teams.…See more Apply machine learning techniques including deep learning frameworks and transformer architectures for ROI detection, content understanding, and feature extraction. Integrate algorithms into production VOD/live streaming workflows and validate impact through A/B testing and objective quality metrics (VMAF, PSNR, SSIM).

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams.…See more Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

Design and build large-scale multimodal foundation models that integrate high-dimensional biomedical imaging with molecular and language data. You will implement cross-domain data fusion strategies, develop high-performance ML pipelines for petabyte-scale datasets, and collaborate with scientists and engineers to translate biological complexity into scalable, production-ready code.…See more The role requires deep expertise in Computer Vision architectures, distributed training frameworks, and expert Python proficiency. You will contribute through high-impact publications or open-source work and demonstrated ability to handle the noise and sparsity inherent in biological data.