Machine Learning Algorithm Engineer, Silicon

Minimum qualifications:

• Bachelor's degree in Electrical Engineering or Computer Science, or equivalent practical experience.
  
• 3 years of experience with ISP, Machine Learning, and Computational Photography.
  
• Experience in common Machine Learning frameworks (e.g. TensorFlow, Pytorch)
  
• Experience in C/C++ or Python programming.

Preferred qualifications:

• Master’s degree or PhD in Electrical Engineering or Computer Science.
  
• 5 years of experience in image processing, machine learning based image processing, and computational photography.
  
• Experience in real-time imaging use cases.
  
• Experience in machine learning algorithm and hardware design trade-off analysis.
  
• Experience with camera algorithms and architecture.
• Experience with Generative AI model for image/video processing.
  

About the job

Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we've got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google's services. As a Hardware Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

In this role, you will develop emerging key camera use cases by leveraging the computing platform of Google Tensor SoC, exploring new imaging algorithms, and leveraging machine learning technologies.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

Responsibilities

• Research and develop camera video machine learning algorithms for enabling new imaging use cases, leveraging Camera, ISP, and Machine Learning.
  
• Explore and identify a technical direction for new imaging experiences and architecture.
  
• Work with Hardware Architects, Research, Image Quality, and Software teams to identify and develop new video machine learning algorithms, software, hardware partitioning, and hardware acceleration designs.