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DPU Programmer with AI Factory Experience
4 weeks ago
Title: DPU Programmer with AI Factory Experience
Location: REMOTE India
Job Overview:
We are looking for a skilled and motivated DPU Programmer with hands-on experience in AI Factory (AIF) environments. This role involves developing, optimizing, and deploying workloads for Data Processing Units (DPUs)—especially in AI pipelines, smart NICs, and offloading tasks from host CPUs/GPUs.
The ideal candidate should have a deep understanding of DPU hardware, NVIDIA BlueField, AI Factory workflows, and high-performance data flow design for machine learning and inference systems.
Key Responsibilities:
Design and develop DPU-based applications in AI Factory workflows.
Work with NVIDIA DOCA SDK, BlueField DPUs, and DPDK to offload data plane tasks.
Collaborate with AI and infrastructure teams to integrate DPU offloads into AI pipelines.
Optimize performance for data movement, security, and inference offload to DPU.
Implement low-latency, high-throughput DPU code paths using C/C++, Python, and specialized APIs.
Work on orchestrating AI workloads across CPU/GPU/DPU for efficiency and cost-optimization.
Debug and troubleshoot complex hardware-software interaction issues on BlueField or similar DPUs.
Required Skills & Qualifications:
Bachelor's or Master's degree in Computer Engineering, Computer Science, or related field.
Strong experience with DPU programming (preferably NVIDIA BlueField, Marvell, or similar platforms).
Proficiency in C/C++, Python, and experience with DOCA SDK and DPDK.
Understanding of AI Factory architecture (e.g., NVIDIA AIF, orchestration, containerization).
Familiarity with RDMA, NVMe-oF, RoCE, and smart NIC technologies.
Experience with Kubernetes, Docker, and AI/ML model deployment pipelines.
Good grasp of networking stacks, low-latency tuning, and system performance optimization.
Preferred (Nice to Have):
Experience with SmartNIC offloads for inference/vision workloads.
Knowledge of NVIDIA NIM, Triton Inference Server, or DeepStream.
Prior experience integrating with cloud-native AI platforms or AI Factories at scale.
Contributions to open-source AI/DPU libraries.
