Machine Learning Engineer, Computer Vision

GoogleMountain View, CA
8d$141,000 - $202,000

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. 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 be in one or all of the following product families: virtual reality (VR), wearables, phones, and home. 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. The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Requirements

  • Bachelor's degree in Electrical Engineering, Computer Science, relevant technical field or equivalent practical experience.
  • 2 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).

Nice To Haves

  • Master or PhD degree in Engineering with a focus on Computer Vision or Camera, or equivalent practical experience.
  • 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).

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.
  • Understand and be able to 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.
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