GPU Compiler Eng
2,158 open positions
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Machine Learning System Software Engineer AppleSunnyvale, United States of America 3mo Design and implement APIs for Apple's Neural Engine to enable high-performance, low-power AI execution on Apple devices.
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Senior Software Engineer - Image and Data Processing Libraries NVIDIAUS, CA, Santa Clara $224k3mo Design, develop, and optimize GPU and CPU accelerated software libraries (nvComp, NPP, nvJPEG, etc.) for AI, data analytics, image processing, and scientific simulations.
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SOC Performance Engineer Advanced Micro Devices, IncAustin, Texas 3mo Analyze and optimize the architectural performance of AMD's PC and Gaming processors by tracing workloads, modeling hardware platforms, and debugging SOC issues.
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Software Engineering Manager, ML Kernel Performance, AWS Neuron, Annapurna Labs
AmazonToronto, Ontario, Canada
CA$171k–CA$286k3mo
Architect and implement high-performance compute kernels for ML operations on AWS custom accelerators (Inferentia/Trainium), optimizing deep learning and GenAI workloads at the hardware-software boundary.
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Staff Applications Engineer ArmMultiple locations 3mo Support Arm's partners in building real-world applications for Edge and Physical AI using Computer Vision and Machine Learning software solutions.
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Staff CPU Microarchitect, Vector and Matrix Compute TenstorrentRemote $100k3mo Designing next-generation high-performance RISC-V CPU Vector (RVV), Floating Point, and Matrix extensions to enable efficient execution of HPC and AI inference/training workloads.
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Machine Learning Systems Engineer MotionalRemote $144k3mo Build and optimize core systems enabling researchers to train frontier models at scale, focusing on speed, cost, reliability, and throughput.
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(Sr./Staff) Software Engineer, Edge AI - Toolchain↗ Omnivision 3mo Architect and enhance toolchains for Neural Network solutions on Video Processor roadmaps, enabling customers and partners to develop and port AI models to run optimally on Neural Processing Units (NPUs).
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Bachelor Thesis - Artificial Intelligence in Microcontroller (f/m/div)↗ Infineon TechnologiesVillach, Carinthia, Austria 3mo Develop AI algorithms and optimize models for edge hardware (microcontrollers) to enable event/data-efficient inference and real-time integration of sensing, compute, and comms.
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Software Engineer, Compilers, Runtimes and Toolchains, Early Career↗
GoogleMexico City, Mexico
3mo
Develop features in LLVM optimization and code generation to support build scalability, toolchain velocity, peak performance, and safety for Google developers.
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Lead SDE C/C++ Hardware/Software Co-Design, Machine Learning Acceleration Systems
AmazonCupertino, California, United States
$193k–$262k3mo
Develop bare metal firmware and custom hardware for AWS ML accelerator chips to enable neural network model execution.
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Senior Field Application Engineer InnateraRemote 3mo Senior Field Application Engineer supporting product development and customer implementation for ultra-efficient neuromorphic processors for AI at the edge.
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Staff Software Engineer, Inference CoreWeaveLondon, England £116k3mo Design and operate a Kubernetes-native inference platform for massive-scale GPU workloads, focusing on low-latency optimization, cost efficiency, and reliability for AI/ML, VFX, and real-time inference.
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Serbia- AI Workloads Engineer NextSiliconBeograd, Serbia 3mo Build workflow modeling infrastructure and adapt open-source AI systems to drive performance improvements on NextSilicon's next-generation HPC and AI hardware platforms.
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Senior Neuromorphic Researcher↗ GradiantRemote €32k3mo Conduct research on third-generation artificial neural networks, synaptic plasticity, and energy-efficient parallelism for AI-on-the-edge use cases.
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Senior Field Applications Engineer - Edge AI NxpShanghai (Pudong), CN 3mo Drive demand creation and customer design-in for NXP's application processors, AI accelerators, and related solutions while providing technical support to sales teams and customers.
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Principal Software Engineer MicrosoftUnited States, Washington, Redmond 3mo Design and build GPU-accelerated infrastructure for training and inference workloads, managing device scheduling, isolation, and sharing across bare metal, VMs, and containers.
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