Machine Learning Engineer, LLM, Personal AI, Google Pixel

2 Weeks ago • 2-4 Years • Artificial Intelligence

Job Summary

Job Description

This role involves developing machine learning systems and models for Google's Pixel personal agent. Responsibilities include data collection design, data engineering, feature engineering, model training, and evaluation. The engineer will collaborate with engineers, researchers, and product managers to implement new features. This position requires Android/Pixel application development, decomposing use cases into technical problems, maintaining machine learning models, designing evaluation frameworks, and staying current with machine learning techniques. The ideal candidate will propose, design, and implement data collection solutions, ensuring data cleanliness for model tuning and evaluation.
Must have:
  • Bachelor's degree or equivalent experience
  • 2 years software development experience (Python, C++)
  • Machine learning experience
  • Develop and maintain ML models
  • Design evaluation frameworks
  • Data collection and cleaning
Good to have:
  • Master's/PhD in Computer Science
  • Experience in Android development
  • NLP, LLM, or Computer Vision expertise
  • Strong Python/C++ skills

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++, etc.).
  • Experience with machine learning.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 2 years of experience with applied machine learning/machine learning research.
  • Experience in Android development.
  • Expertise in NLP, LLM, or Computer Vision.
  • Strong programming skills in Python, C++.
  • Excellent teamwork, problem-solving, and analytical skills.

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 position, you will be responsible for developing 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 and decompose use cases into tractable technical problems.
  • Develop and maintain machine learning models.
  • Design evaluation framework and carry out evaluations of the machine learning models.
  • Stay up-to-date on the latest machine learning techniques and technologies and apply them to our technical solutions.
  • Propose, design, and implement data collection solutions, collect and clean data to tune and evaluate machine learning models.

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