Applied Machine Learning Engineer

1 Month ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

This role involves partnering with DeepMind and CoreML to integrate the Gemini model into mobile applications. The Applied Machine Learning Engineer will create and deploy innovative Generative AI features for Android, focusing on high-quality, user-centric solutions. Responsibilities include launching and scaling Generative AI models for critical Android use cases, ensuring optimal performance and user satisfaction through model evaluation. The ideal candidate will have experience with ML infrastructure, data structures/algorithms, and software development (Python, C++). Experience with Generative AI, Mobile Development, and Deep Learning is preferred. The role requires expertise in building and deploying machine learning models, focusing on performance and user experience within the Android ecosystem.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development (Python, C++)
  • 2+ years experience with data structures/algorithms
  • 1+ year ML infrastructure experience (deployment, evaluation, optimization)
  • Partner with DeepMind and CoreML
  • Create and deploy Generative AI features
Good to have:
  • Master's/PhD in Computer Science
  • Experience with Machine Learning/Deep Learning
  • Experience with Generative AI or Generative Modeling
  • Experience with Mobile Development

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages (e.g., Python, C++), or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience with Machine Learning or Deep Learning.
  • Experience with Generative AI or Generative Modeling.
  • Experience with Mobile Development.

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's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

  • Partner with DeepMind and CoreML to bring the Gemini model to mobile applications.
  • Create and deploy innovative Generative AI features that redefine the mobile experience.
  • Utilize Machine Learning expertise to build high-quality, user-centric solutions for Android.
  • Launch and scale Generative AI models to power critical use cases across the Android ecosystem.
  • Ensure optimal performance and user satisfaction through comprehensive model evaluation.

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