Todd Farr
About Todd Farr
Todd Farr is a Functional Lead in Manufacturing Automation and Hardware Testing, currently working at Ouster in the San Francisco Bay Area. With over 14 years of experience in designing and deploying automated manufacturing systems, he has held various engineering roles at notable companies including PAX Labs, Nike, and Apple.
Current Role at Ouster
Todd Farr serves as the Functional Lead for Manufacturing Automation and Hardware Test at Ouster. He has held this position since 2022, contributing to the company's initiatives in advanced manufacturing processes. His role involves overseeing the integration of automation technologies and ensuring the efficiency of hardware testing protocols within the manufacturing environment.
Previous Experience at Ouster
Prior to his current role, Todd Farr worked at Ouster as a Senior Manufacturing Engineer specializing in Automation for a period of six months in 2022. During this time, he focused on enhancing the automation capabilities within the manufacturing processes, applying his extensive background in engineering to support the company's operational goals.
Professional Background
Todd Farr has over 14 years of experience in designing, developing, and deploying advanced automated and semi-automated manufacturing systems. His career includes significant roles at various companies, such as PAX Labs, Nike, Apple, and LabelOne Connect, where he has developed expertise in machine design and engineering management.
Education and Training
Todd Farr studied Mechanical Engineering at Brigham Young University - Idaho, where he earned a Bachelor of Science (BS) degree. He furthered his education by completing a Nanodegree in Machine Learning Engineering from Udacity in 2016, which enhanced his skills in data science and machine learning techniques.
Skills and Expertise
Todd possesses strategic planning and project management skills, particularly in managing complex stakeholder engagements. His expertise spans front and backend software development, as well as data science and machine learning techniques. This diverse skill set supports his work in engineering, innovation, and invention.