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Overview In this AI Partner Solution Sales role within the Enterprise Partner Sales team, you orchestrate strategic collaboration between Microsoft and leading AI partners to unlock transformational outcomes for…
About Agoda At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to…
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea…
A Technical Program Manager coordinates hardware-AI projects, bridging FuriosaAI’s engineering teams with global manufacturing partners to deliver AI compute solutions, ensuring technical alignment and on-time delivery.
Develops and maintains low-level firmware for AI-native SoCs, including ROM code, bootloaders, and secure boot, while collaborating with hardware teams on SoC bring-up and validation.
Develops firmware/software for NPU management interfaces, handling communication between host systems and AI accelerators. Focuses on power, performance, and thermal telemetry, protocol compliance (MCTP/PLDM), and system-level validation for AI hardware.
Develop and maintain Linux PCIe device drivers and kernel modules for FuriosaAI's AI-native compute platform, optimizing DMA, IOMMU, and high-performance I/O pipelines.
Develops firmware/software for NPU management interfaces, handling communication between host systems and AI accelerators via protocols like MCTP/PLDM, while ensuring telemetry, health monitoring, and compliance with industry specs.
This role involves creating and maintaining developer-facing documentation for FuriosaAI's SDK and LLM software stack using a docs-as-code approach. The engineer will build automated validation pipelines to ensure documentation accuracy against live hardware and code releases.
Builds and maintains AI-native compute infrastructure for FuriosaAI’s NPU-based systems, focusing on reliability, observability, and automation to ensure scalable, secure, and efficient production services.
Develops autonomous agent systems that solve complex engineering problems via AI-driven exploration, optimization, and self-improvement, integrating LLM post-training and multi-agent workflows for production-grade solutions.
Design PyTorch-native kernel integration layers and runtime environments to execute custom AI kernels efficiently within PyTorch, optimizing for hardware control and tensor programmability.
FuriosaAI is seeking a Software Engineer to design and implement high-performance kernels for their proprietary AI-native compute platform. The role involves optimizing AI model performance on hardware, developing diagnostic tools, and enabling end-to-end programming for AI workloads.
FuriosaAI is seeking a Software Engineer to develop middle-end compiler optimizations for their AI inference hardware. The role involves designing IR abstractions, scheduling algorithms, and performance models to improve the efficiency of deep learning workloads on specialized compute platforms.
FuriosaAI is seeking a Software Engineer to develop the front-end of their AI compiler, focusing on model ingestion, graph-level optimizations, and the design of a tensor-level kernel language. The role involves translating deep learning models into internal representations and collaborating on compiler infrastructure to maximize performance on AI hardware.
FuriosaAI is seeking a Software Engineer to develop AI reference applications and maintain internal services to support their AI-native compute platform. The role involves building RAG and agentic systems, creating sample code, and collaborating with the global developer community.
Builds and optimizes an agent system framework for AI-driven automation, integrating LLM-based reasoning, tool execution, and orchestration in a production environment.
FuriosaAI is seeking a Senior Solution Architect to bridge the gap between technical teams and customers by designing AI inference architectures and optimizing pipelines on their proprietary NPU hardware. The role involves conducting PoCs, performing performance benchmarks, and providing technical support to ensure successful deployment of AI applications.
Build and optimize a high-performance inference engine for LLMs and multimodal models on FuriosaAI’s NPUs, collaborating with compiler and hardware teams to maximize throughput and efficiency.
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