2021 Machine Learning for Controls Internship at Blue River Technology
🇺🇸 United States › California › Sunnyvale (Posted Mar 23 2021)
Blue River Technology serves the agricultural industry by designing and building advanced farm machines that utilize computer vision and machine learning to enable farmers to understand and manage every plant. These machines help farmers to improve profitability, protects the environment by reducing pesticide use, and captures valuable plant-by-plant data. Blue River is a pioneer in the agricultural robotics space and has developed the See & Spray precision sprayer, which applies pesticide only where needed, and can reduce pesticide use 90%.
John Deere & Company, with over 180 years of experience in designing, manufacturing, and distributing innovative products to farmers, acquired Blue River Technology in the fall of 2017 as an independently run subsidiary. In partnership with John Deere, Blue River has expanded rapidly and together both companies see many opportunities to apply advanced computer vision, machine learning, and robotics technologies to other areas in agriculture beyond spraying.
Our office is located in Sunnyvale, CA and is home to 100+ team members with diverse experience including computer vision, machine learning, systems software, autonomous vehicles and precision agriculture. Our working environment is fast paced and highly collaborative, and employees are excited to use their talents to improve food production and protect the environment.
Summary and Responsibilities
We are looking for a highly skilled engineer/scientist at the cutting edge of control systems and machine learning to push the boundaries of application onto big robots. You will be joining a world-class research and engineering team to provide critical skills in improving existing systems from fundamental understanding to implementation on robot. The role will include work in the following areas:
Work on developing the fundamentals of learning based control applied to hardware (i.e. big robots).
Bring a breadth of classical and modern controls knowledge and systems thinking.
Benchmark existing model based and model free control approaches and participate in improving existing methods.
Enrollment in or completion of degree program in Computer Science or related fields
Experience working with machine learning systems, with particular emphasis on reinforcement learning
Attention to detail and ability to work independently
A positive attitude and willingness to take on a variety of tasks as necessary
In addition, the following are a plus:
Enrollment in or completion of advanced degree, e.g., M.S., Ph.D.
Strong applied skills in Python, C++, Hardware, Linux, Modern Controls, Classical Controls & Math
Up to date on current research papers and modern controls methods
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