Uhnder has developed the world’s first automotive digital Radar on Chip (RoC).  Sensors based on Uhnder’s Digitally Coded Modulation (DCM) technology achieve new and unprecedented levels of performance for advanced driver assistance systems (ADAS) and autonomous driving solutions.  Founded in 2015, its main engineering operations center is in Austin, Texas, USA with design facilities in India and China. 

As Radar Applications Engineer, you will join a team of industry experts spanning mixed-signal, RF, digital, systems, and software experts to develop the next generation of electronics surrounding us and impacting us in our everyday lives. 

Essential Functions 

  • Create a set of high-quality, informative, and accurate product documents for radar silicon and sensors, including

    • Product user guides and reference manuals

    • Application notes, and white papers with software projects

    • Marketing presentations, and blogs

  • Document and deliver radar software demos

  • Work closely with field applications, sales, systems, and engineering groups to align customer requirements and use-cases to internal documentation, demo, and development activities

  • Support evaluation of sensors prior to production with test and data analysis

  • Drive application activity and planning for conferences, webinars, and website 

  • Track industry trends, innovations and identify new related opportunities 

Required Education and Experience: 

  • BS in EE with 5+ years of relevant experience; MS preferred 

  • Evidence of delivering high-quality, detailed documentation, application notes, white papers, & marketing collateral

  • Knowledge of and experience with automotive radar sensors or communications systems

  • Basic programming knowledge in C/C++, Python

  • Experience in real-time, embedded, performance-critical, applications (e.g. automotive, communications, etc.)

Preferred Experience

  • Experience in automotive ADAS, autonomous, and/or robotic applications

  • Development of system/SW demos and proof of concepts

  • Knowledge of perception algorithms (e.g. tracking, fixation, fusion, environmental modeling, machine learning, etc.) 

  • Collaboration with field and engineering team

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