Google Hiring for Camera Test Engineer, Central Test Engineering, Machine Learning at Mountain View, CA Full Time
Minimum qualifications:
- Master’s degree in Engineering, Computer Science, Imaging Science or relevant field with an emphasis on computer vision and Machine Learning or equivalent practical experience.
- Experience with Python, Unix, and C++.
- Ability to travel up to 20% of the time as required.
Preferred qualifications:
- PhD degree in Engineering, Computer Science, Imaging Science, or relevant field with an emphasis on computer vision and Machine Learning.
- Experience with training learning neural networks and building the system from prototyping to production.
- Experience with Machine Learning framework (e.g. TensorFlow) and setting up model deployment environment using Docker.
- Experience with testing and building consumer electronics products from product introduction (NPI) to mass production.
- Knowledge in image processing algorithm and computer vision (e.g., image registration, segmentation, classification, object detection, supervised and unsupervised learning).
- Knowledge with data structure and algorithms.
About the job
At Google, our philosophy is build it, break it and then rebuild it better. That thinking is at the core of how we approach testing at Google. Unlike roles with similar names at the other companies, Test Engineers at Google aren’t manual testers – you write scripts to automate testing and create tools so developers can test their own code. As a Test Engineer, you navigate Google’s massive codebase, identify weak spots and constantly design better and creative ways to break software and identify potential problems. You’ll have a huge impact on the quality of Google’s growing suite of products and services.
As a Camera Test Engineer on the CTE team, you will manage the testing of the functional performance of camera devices. You will also work on Vision Machine Learning projects in Google Device and Services product area.
Google’s mission is to organize the world’s information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user’s interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people’s lives better through technology.
Responsibilities
- Design camera based automated optical inspection (AOI) stations including both hardware and software for factory test with a focus on assembly defects detection.
- Develop entire computer vision solutions and collaborate with cloud machine learning (ML) team to invent machine and deep learning algorithms for production line from NPI to mass production stage.
- Work with cross-functional teams including assembly engineer and Product Development team to define test coverage and develop corresponding ML based defect detection algorithm.
- Deploy the ML models and integrate into test station scripts. Analyze the build data (yield, overkill, escape rate) to improve the detection algorithm accuracy and stabilize station hardware setup involving camera optics and lighting condition.
- Work with original equipment manufacturer, original device manufacturer, joint development manufacturer, and contract manufacturer partners to ensure test station are deployed across different factories.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.