Software Engineer II, Machine Learning

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  
• 1 year of experience with data structures or algorithms.
  
• 1 year of experience with Machine Learning (ML) algorithms and tools (e.g., TensorFlow), Artificial Intelligence (AI), Deep Learning or Natural Language Processing.
  

Preferred qualifications:

• Experience in Machine Learning in the field of Multimodality or related fields like Computer Vision or Video/Image Processing.
  
• Experience with Natural Language Processing, Computer Vision, Machine Learning, Research Publications.

About the job

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.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities

• Develop models for automatic evaluation of text/image and text/video alignment.
  
• Develop models for image/image frame/frame consistency in image sequence and video generation.
  
• Apply models for improving multimodal generation, including caption generation, image and video generation and multimodal instruction following.