Platform Application Engineer (DPDK/Cloud-native/AI), Intel

Karnataka, India, Bangalore
April 28, 2026
Full Time

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Job Description

Intel is hiring a Platform Application Engineer (DPDK/Cloud-native/AI) to join its Data Center Group in Bangalore. The engineer will create high-speed packet processing solutions through Intel Architecture and DPDK technologies. The engineer will help customers improve their networking applications through support work which includes AI developer tool integration and migration of packet processing systems to cloud native environments.

Job ID: JR0281304

Qualification: B.E./B.Tech./M.E./M.Tech./M.C.A./MS in Computer Science, Networking, Electronics, or related field

Experience: 5 – 10 years

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Main Duties

  • Support customers in building high performance packet processing applications using DPDK frameworks and Intel architecture platforms.
  • Provide technical consulting to developers porting and optimizing networking workloads across Intel multicore communication processors.
  • Develop demonstrations, benchmarks, and reference architectures for networking solutions on Intel Xeon and Atom processors.
  • Prepare technical documentation including application notes, white papers, and presentations explaining networking architectures and solutions.
  • Assist customers migrating packet processing workloads from bare metal systems to scalable cloud native environments.

Essential Qualifications

  • Strong programming expertise in C language development on Linux systems for performance critical networking software.
  • Hands-on experience using DPDK frameworks and virtualization technologies on Intel x86 architecture platforms.
  • Knowledge of networking protocols including Ethernet, IPv4, IPv6, TCP, UDP, and application layer communication protocols.
  • Experience developing packet processing solutions on network processors, multicore systems, or Intel communication platforms.
  • Understanding of containerization technologies such as Docker and orchestration platforms including Kubernetes environments.

Preferred Skills

  • Acquired knowledge about neural network architectures which include MLP and CNN and ResNet. 
  • Knowledge about machine learning frameworks which include PyTorch and TensorFlow and Keras for AI model development. 
  • Practical experience with AI model formats which include ONNX and PyTorch .pt files and TensorFlow deployment models. 
  • Execute AI models from local and remote locations while developing inference pipelines through API integration. 
  • AI assisted developer tools which include GitHub Copilot and Microsoft Copilot and ChatGPT and Claude.

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