Software Engineer II, YouTube Trust and Safety

2 Months ago • 1 Years + • Artificial Intelligence

Job Summary

Job Description

As a Software Engineer II at YouTube Trust and Safety, you'll build infrastructure for processing videos post-classification, encompassing model calibration and enforcement. Responsibilities include contributing to gating infrastructure and multi-agent Large Language Model (LLM) workflows. You'll also maintain existing infrastructure for automated model releases and calibration, as well as implement first-party Client Generative AI protections. The role requires experience in software development (Python, C++, Java, JavaScript etc.), data structures, algorithms, and Machine Learning (TensorFlow). You'll work on projects critical to Google's needs, with opportunities for team and project changes. The ideal candidate will be versatile, a leader, and enthusiastic about full-stack challenges.
Must have:
  • Bachelor's degree or equivalent experience
  • 1 year software development experience (Python, C++, Java, JavaScript)
  • 1 year experience with data structures/algorithms
  • 1 year experience implementing core ML concepts
  • TensorFlow experience
  • Contribute to gating infrastructure and/or LLM workflows
  • Maintain existing infrastructure (model releases/calibration)
Good to have:
  • Experience in applied machine learning at scale
  • Experience with TFlex
  • Experience in Colaboratory, C++
  • Microservices experience
  • Distributed systems experience

Job Details

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 implementing core Machine Learning (ML) concepts.
  • Experience in TensorFlow.

Preferred qualifications:

  • Experience in applied machine learning at scale.
  • Experience in designing, analyzing, launching and serving Machine Learning (ML) models preferably with TFlex.
  • Experience in Colaboratory, TensorFlow, C++, Python.
  • Familiarity with micro-services and issues and solutions specific to such systems, like failures/retries, latency distributions and request hedging, replication delays, etc. and building distributed systems.

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 will be building infrastructure for processing videos after their classification. This includes model and calibration, enforcement.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

Responsibilities

  • Contribute towards our gating (e.g., video selection) infrastructure and/or the multi-agent Large Language Model (LLM) workflows.
  • Learn and step in to maintain existing infrastructure (automated model releases/calibration, first-party Client Generative AI protections).

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