Milpitas, CA 95035
Full-time


About Gyrfalcon Technology (www.gyrfalcontech.com):

This innovative semiconductor technology company is transforming the complexities of Artificial Intelligence hardware into a simple platform, to make Artificial Intelligence Productizations possible. The company is the world’s leading developer of low-cost, low-power, high-performance Artificial Intelligence (AI) processors.

Founded by veteran Silicon Valley entrepreneurs and Artificial Intelligence scientists, Gyrfalcon Technology aims to expand the power of cloud Artificial Intelligence to local devices with greater performance and efficiency, and to make Artificial Intelligence Productization possible. Gyrfalcon Technology was funded by world-class financial and strategic investors from U.S., China, Japan and Korea.

Description

As an embedded software application engineer, you are responsible for developing software for the company’s AI chips and validating new chip designs.

Responsibilities

Design and implement low-level software of chips and systems from beginning to production and commercial deployment.

Develop SDK for all company chips, optimize SDK overall performance, provide sample applications to customers.

Formulate test plans for chip validation and system performance measurement.

Interface with system hardware design, chip development, and AI Algorithm teams.

Support worldwide FAE/Sales team’s activities.

Qualifications

BA/BS degree in computer science, electrical engineering, or related technical fields.

Working experience with embedded microprocessor or semiconductor companies are preferred.

Minimum 8 years of industry experience with C/C++, Python, and object-oriented programming.

Experience with programming real-time systems or other embedded systems.

Experience with consumer electronic product development, such as STB, camera, car entertainment system, mobile phone, etc.

Expertise with Linux kernel, device drivers, Android and Windows programming.

Familiarity with low-speed interfaces including UART, SPI, and I2C, and high speed interfaces such as USB, EMMC, SDIO, PCIe, MIPI, etc.

Experience with reading hardware schematics and using common tools including scopes, logic analyzers, emulators, and signal generators.

Experience with or knowledge of neural networks, artificial intelligence, TensorFlow framework, etc.

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