Job Details: Job Description: Intel is seeking a highly motivated Platform Application Engineer (PAE) with deep expertise in DPDK based packet processing and a strong drive to leverage emerging AI driven engineering technologies. The role requires an engineer with a steep learning curve, someone who proactively leads the adoption of new technologies-particularly AI/ML tools and workflows-and integrates them effectively into existing customer solutions. The ideal candidate is passionate about performance critical networking software, excels in hands on problem solving, and is eager to pioneer the use of modern AI capabilities to enhance productivity, debugging, and next generation packet processing architectures. Key Responsibilities • Support and guide customers in developing high performance packet processing applications on Intel Architecture using DPDK, Intel drivers, firmware, and related software stacks. • Act as a trusted technical consultant to third party developers, enabling them to port, optimize, and scale their applications on Intel platforms. • Develop demonstrations, benchmarks, reference designs, and prototype applications on multicore communication processors (Xeon, Atom). • Prepare high quality customer facing documentation, including Application Notes, White Papers, Device Advisories, and technical presentations. • Serve as the first technical point of contact for customer software integration and bring up activities. • Act as a technical bridge between Intel's engineering teams and customer teams, ensuring timely issue resolution and architectural alignment. • Reproduce, root cause, and report issues to relevant design teams; propose workarounds where feasible. • Collaborate with Intel's development, marketing, program management, and telecom application teams to define and promote optimal customer solutions. • Deliver training, debugging support, and onsite integration assistance as required (some travel expected). • Support the transition of bare metal packet processing applications to cloud native architectures Qualifications: Qualifications • B.E. / B.Tech. / M.E. / M.Tech. / M.C.A. / MS (Computer Science, Networking, Electrical, Electronics and Communication, or related fields). • Experience: 5 to 10 years. ________________________________________ Skills and Expertise Required Communication and Core Engineering Skills • Strong oral and written communication skills. • Strong development, debugging, and problem solving abilities. Networking and Protocols • Knowledge of Datacom protocols: o Ethernet o IPv4 / IPv6 o TCP / UDP o Application layer protocols • Understanding of Switching and Routing. Programming and Platform Expertise • Strong programming experience with C on Linux. • Experience with DPDK and virtualization on Intel x86 platforms. • Experience in data plane packet processing on Network Processors, Multicore SoCs, or Intel multicore platforms. • Knowledge of microprocessor architecture. • High level understanding of Telecom Networks (3G, LTE, 5G). Cloud Native Expertise Hands on experience in deploying cloud native Applications using: • Containerization (Docker/Container) • Orchestration (Kubernetes) • Microservices architectures AI/ML Model Development and Deployment Fundamentals 1. High-level knowledge of Neural Network Architectures (MLP, CNNs, ResNets) 2. Knowledge of model evaluation metrics, including accuracy, precision/recall, F1 score, latency, and throughput 3. Familiarity with common deep learning frameworks such as PyTorch, TensorFlow, and Keras 4. Experience with model exchange and serialization formats (e.g., ONNX, PyTorch .pt, TensorFlow .pb) 5. Experience running AI/ML models on local or remote machines and interacting with them via APIs. AI and ML Tools • Hands on experience using AI assisted developer tools, including: o GitHub Copilot o Microsoft Copilot o ChatGPT o Claude For tasks such as information retrieval, debugging, and code generation.

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