About the job
As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The scope of the Central Test Engineering team spans hardware and software, and across engineering and operations as the team that knows the secrets to successfully shipping high-volume consumer products while balancing engineering and operational priorities. In this role, you will own one of the key consumer satisfaction metrics such as functional performance of the device. As a key member of the cross-functional team that will launch the product, you will be an integral part of Google's hardware success. You will use your computer vision experience to develop multiple machine learning based automatic optical inspections stations for production lines.
Responsibilities
Develop solutions in artificial intelligence and machine learning applications for smart manufacturing.
Implement and adapt deep learning architecture and the goal to land the factory test stations with a focus on automatic optical inspection solutions for production lines from new product introduction (NPI) to mass production (MP) stage.
Debug the computer vision or image processing algorithms to investigate camera or assembly failures.
Design and develop components of scalable Machine Learning infrastructure for manufacturing.
Maintain and improve existing AI platform to support advanced automatic optical inspection.
Qualifications
Minimum
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages (e.g., Java, Python, C/C++).
Experience with image processing, computer vision, and machine learning algorithms.
Experience with machine learning computer vision algorithm development and tools (e.g., tensorflow, flume, machine learning libraries), artificial intelligence, deep learning.
Experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
Preferred
Master's degree or PhD in Engineering with a focus on computer vision or camera.
Experience in building and testing consumer electronic products for manufacturing including design for manufacturing (DFM) and design for test (DFT).
Experience in building machine learning powered automatic-optical-inspection (AOI) systems including hardware, software, and algorithms.
Experience with Machine Learning infrastructure (e.g., model deployment, model evaluation, model serving, data processing, debugging, fine tuning).
Experience with generative AI and LLM related skills (e.g. Gemini AI suite, Vertex AI).
Ability to travel domestically or internationally up to 20% of the time as needed.