Image Quality Expert, AI Research
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In-office locations: Mountain View, CA, USA.
Remote location(s): California, USA.
Minimum qualifications:
- 2 years of experience working as an image quality domain expert with a team of engineers or researchers developing camera software.
- Experience capturing training data for ML models or generative AI.
- Experience with data curation and annotation for AI training.
- Experience in photography covering several fields.
Preferred qualifications:
- Ability to articulate and communicate visual concepts.
- Excellent video editing skills.
- Excellent image processing skills with attention to detail.
About the job
Elevating the image quality and user experience of generative Artificial Intelligence and Machine Learning models (AI and ML) through meticulous evaluation, data collection and curation, and insightful beta testing.In this role, you will make aesthetic decisions when delivering qualitative and quantitative feedback during development. You will contribute to product strategy by identifying emerging trends and opportunities.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.
Responsibilities
- Provide qualitative and quantitative feedback on tuning, algorithmic changes, and generative AI model iterations that affect image quality.
- Collect training data and photos for generative AI/ML models, and algorithms.
- Curate datasets and evaluation sets for feature development.
- Beta test and evaluate real-time effects to improve features and find bugs to avoid negative brand impact/reviews.
- Help define product opportunities and set direction (e.g., identify emerging trends, identify gaps between casual smartphone and professional photography, etc.).
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