Senior RF Application Engineer

1. Customer Support & Consultation

• Provide pre-sales and post-sales support to customers, assisting them with FPGA design and integration.
• Analyse customer requirements and work with internal engineering teams to design customized FPGA solutions.
• Assist customers in FPGA-based system design, helping them select appropriate devices and development tools.
• Offer on-site and remote technical support, troubleshooting, and debugging FPGA designs and hardware.

1. Design & Development

• Assist customers in implementing FPGA designs, including writing and optimizing VHDL/Verilog code, implementing IP cores, and integrating FPGA designs into larger systems.
• Help customers with FPGA toolchains such as Xilinx Vivado, Intel Quartus, and other relevant EDA tools.
• Develop reference designs and demo applications to showcase FPGA solutions for specific customer use cases.
• Collaborate with R&D teams to continuously improve FPGA product offerings and solutions.

1. Training & Documentation

• Conduct technical seminars, workshops, and training sessions to educate customers on FPGA technologies, design flow, and best practices.
• Create and maintain user-friendly technical documentation, application notes, and whitepapers to help customers with their FPGA implementation process.

1. Product Feedback & Market Insights

• Collect and communicate customer feedback on product features, requirements, and issues to the product management and engineering teams.
• Assist in the development of new FPGA products or features based on customer needs and market trends.
• Stay up-to-date with the latest FPGA technology trends, tools, and industry best practices.

Requirements:

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related field.
• Minimum of 3-5 years of hands-on experience in FPGA design and implementation, with a strong understanding of digital logic and hardware description languages (HDL) such as VHDL or Verilog.
• Experience with FPGA development tools such as Xilinx Vivado, Intel Quartus, or similar platforms.
• Knowledge of embedded systems, including microcontrollers, processors, and communication protocols (e.g., SPI, I2C, PCIe, Ethernet).
• Familiarity with high-performance computing (HPC) applications or machine learning (ML) acceleration using FPGA.

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