Platform Application Engineer (dpdk/cloud-native/ai)

Intel Intel · Semiconductors · Bangalore, India

This role focuses on supporting customers in developing high-performance packet processing applications on Intel Architecture using DPDK and related software stacks. It involves acting as a technical consultant, developing demonstrations, benchmarks, and reference designs, and providing customer-facing documentation and support. The role also requires transitioning bare metal applications to cloud-native architectures and leveraging AI/ML tools for productivity enhancement, debugging, and code generation.

What you'd actually do

  1. Support and guide customers in developing high performance packet processing applications on Intel Architecture using DPDK, Intel drivers, firmware, and related software stacks.
  2. Act as a trusted technical consultant to third party developers, enabling them to port, optimize, and scale their applications on Intel platforms.
  3. Develop demonstrations, benchmarks, reference designs, and prototype applications on multicore communication processors (Xeon, Atom).
  4. Prepare high quality customer facing documentation, including Application Notes, White Papers, Device Advisories, and technical presentations.
  5. Support the transition of bare metal packet processing applications to cloud native architectures

Skills

Required

  • B.E. / B.Tech. / M.E. / M.Tech. / M.C.A. / MS (Computer Science, Networking, Electrical, Electronics and Communication, or related fields)
  • 5 to 10 years experience
  • Strong oral and written communication skills
  • Strong development, debugging, and problem solving abilities
  • Knowledge of Datacom protocols: Ethernet, IPv4 / IPv6, TCP / UDP
  • Understanding of Switching and Routing
  • 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)
  • Hands on experience in deploying cloud native Applications using Containerization (Docker/Container), Orchestration (Kubernetes), Microservices architectures
  • High-level knowledge of Neural Network Architectures (MLP, CNNs, ResNets)
  • Knowledge of model evaluation metrics, including accuracy, precision/recall, F1 score, latency, and throughput
  • Familiarity with common deep learning frameworks such as PyTorch, TensorFlow, and Keras
  • Experience with model exchange and serialization formats (e.g., ONNX, PyTorch .pt, TensorFlow .pb)
  • Experience running AI/ML models on local or remote machines and interacting with them via APIs
  • Hands on experience using AI assisted developer tools, including GitHub Copilot, Microsoft Copilot, ChatGPT, Claude

Nice to have

  • Intel drivers, firmware, and related software stacks
  • Application layer protocols
  • Intel multicore platforms
  • AI/ML Model Development and Deployment Fundamentals

What the JD emphasized

  • deep expertise in DPDK based packet processing
  • steep learning curve
  • proactively leads the adoption of new technologies
  • integrates them effectively into existing customer solutions
  • passionate about performance critical networking software
  • eager to pioneer the use of modern AI capabilities
  • 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