Camera Software Engineer, Machine Learning

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, C++, Machine learning techniques, Python Programming, UI design, UX design

Job Description

Minimum qualifications:

• Bachelor’s degree in Computer Science or Electrical Engineering, or a related field, or equivalent practical experience.
• 5 years of experience with software development in C++ or Python with data structures or algorithms.
• 3 years of industry experience in developing software products, and 1 year of experience with software design and architecture.
• 3 years of experience in image processing, machine learning or computational photography.

Preferred qualifications:

• Experience in phone product development.
• Experience in camera 3A (e.g., auto white balance, auto exposure, auto focus) software and algorithm development.
• Experience in Tensorflow.
• Knowledge of color tuning.
• Excellent investigative and problem-solving skills for debugging code, optimizing algorithms, and troubleshooting technical issues.

About the job

Our team develops advanced algorithms and software systems to improve Pixel camera color photography experience, especially in tuning efficiency and accuracy. We launch exciting research projects into each year’s Pixel camera and make an immediate impact on Pixel phone users across the world.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

Responsibilities

• Develop machine learning based automation system or algorithms for auto white balance, color tuning, and quality evaluation.
• Participate in camera auto white balance, color tuning, and image quality evaluation.
• Collaborate with software teams and hardware teams to improve image quality.