Embedded Machine Learning Intern for Sensors and Edge Devices
Sunnyvale, CA, United States
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Bosch Group
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The Bosch Research and Technology Center focuses on the following topics: ASIC design and microsensor system technology; energy conversion and energy storage technologies, modeling simulation and controls; wireless technologies; internet technologies; algorithms for robotics, autonomous systems and data mining; and user interaction technologies. By choice, we are an Equal Opportunity Employer committed to a diverse workforce.
The Microsensor System Technologies Group at the Robert Bosch – Research and Technology Center (RTC) in Palo Alto focuses on solving key challenges that will lead to the next generation of MEMS sensor devices. Strong collaboration with researchers and labs at Stanford University and The University of California at Berkeley combined with the innovative spirit of the Silicon Valley have helped the group in deftly tackling several significant research projects.
Job Description
The purpose of an Intern within the Sensor Systems and ASICs group is to provide support for development and scouting of new sensor system technologies.
The focus of this internship is “on-device learning” and “online classification adaptation and improvement”. As part of the team that specializes in systems and algorithm for new sensor concepts, the Intern is primarily responsible for the simulation, evaluation, and implementation of such machine learning algorithm onto target hardware including micro controllers, FPGAs, edge TPU and Raspberry. The intern will also support the team with research in the field of on-device learning.
Additional tasks include system definition and optimization, design and run of experiments, data gathering and interpretation, performing scouting, documentation, organization, and related tasks at the direction of a research engineer, scientist, or project leader.
Primary Responsibilities:
- Support the team with deployment concepts of standard and nonstandard AI and machine learning algorithm onto resource limited hardware
- Design, build, and maintain developer environments for machine learning
- Design, run, analyze, and manage simulation and provide simulation reports
- Provide scouting support through literature searches, patent searches, industry/academic news searches, academic/business networking, and related activities
- Keep detailed records of activities, and contribute to presentations and written reports
Qualifications
Required Qualifications:
- Pursuing Master’s or Ph.D. degree in Computer Science, Electrical Engineering, or related AI fields
- Practical experience with FPGAs, microcontrollers or related target hardware
- Familiar with common machine learning tools and libraries
- Demonstrated ability to plan, conduct, and manage tasks of medium scope
- Strong personal computer skills including Microsoft and Linux OS
- Excellent oral and written communication skills
Desired Qualifications:
- Last year Ph.D. student with focus on “on device learning” or relevant fields
- Research in sensor related AI and machine learning field with limited resources
- Solid background with TensorFlow, Python and Matlab
- Able to modify machine learning frame works
- Solid with developer environments on Windows and Linux
Additional Information
The U.S. base salary range for this intern position is $37.00-$42.00 hourly. Within the range, individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics)
- FIRST Robotics (For Inspiration and Recognition of Science and Technology)
- AWIM (A World in Motion)
Tags: ASIC Design Classification Computer Science Data Mining Engineering Linux Machine Learning Mathematics Matlab Python Research Robotics STEM TensorFlow
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