Software Engineer III, Machine Learning

3 Months ago • 2-4 Years • Artificial Intelligence

Job Summary

Job Description

This Software Engineer III, Machine Learning role at Google involves developing machine learning systems and models for the Pixel personal agent. Responsibilities include data collection design, engineering, feature engineering, model training, evaluation, and collaboration with engineers, researchers, and product managers. The ideal candidate will have experience in Android development, NLP, LLMs, or Computer Vision, and proficiency in Python and C++. The role focuses on creating and improving features for Google's personal agent, leveraging the latest machine learning techniques.
Must have:
  • Android/Pixel app development
  • Data collection solution design & implementation
  • ML model evaluation framework design & execution
  • Proficiency in Python and C++
  • Experience in applied machine learning
Good to have:
  • Experience in NLP, LLMs, or Computer Vision
  • Master's/PhD in Computer Science or related field

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or a related technical field.
  • 2 years of experience in applied machine learning or machine learning research.
  • Experience in Natural Language Processing, Large Language Models or Computer Vision.
  • Experience in Android Development.
  • Knowledge of programming skills in C++ and Python.
  • Excellent problem-solving and critical thinking skills, along with the passion for teamwork and a respectful approach to collaboration.

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.

In this role, you develop the machine learning system and models that power the Pixel personal agent. This includes tasks such as data collection design, data engineering, feature engineering, model training, and model evaluation. You will work with engineers, researchers and product managers across Google to design and implement new features for the personal agent.

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

  • Develop applications on Android/Pixel.
  • Propose, design and implement data collection solutions.
  • Design evaluation framework and carry out evaluations of the machine learning models.
  • Stay informed on the latest machine learning techniques and technologies and apply them to our technical solutions.
  • Collect and tune data to develop, maintain, and evaluate machine learning models.

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