Software Engineer III, AI/ML, Creator Reputation

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.
  
• 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 2 years of experience with software development in C++, Python and SQL.
• Experience with Data Analysis.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
  
• 2 years of experience with data structures or algorithms.
• Experience developing accessible technologies.
  
• Experience with Big Data Processing.

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.

The team's mission is to empower good creators and safeguard the YouTube ecosystem. We achieve this by understanding creator behavior, identifying bad actors, and developing solutions that have a significant impact on the entire platform. We are not just about keeping the bad actors away, but also about helping good creators thrive.

We deal with complex, ambiguous problems where ground truth is not always available and where abusers are constantly adapting. We look for engineers that enjoy solving hard problems, are comfortable with ambiguity and are passionate about making a difference on a large scale. You will be part of a team that repeatedly finds ways to train successful classifiers and anticipates the next move of the abusers.

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

• Conceive, build, and launch novel ML models and solutions, from initial idea to full production deployment, addressing complex and ambiguous problems.
• Integrate ML classifiers from other teams, harmonizing them into a powerful, cohesive classification system that delivers unified insights.
• Analyze complex problems, such as spikes in abuse or emerging platform vulnerabilities, to devise targeted solutions for mitigation and prevention.
• Collaborate closely with a diverse group of stakeholders across YouTube, including analysts, data scientists, and policy experts, championing data-driven solutions and influencing platform-wide strategies.
• Be comfortable doing some amount of infrastructure work, for example, to launch an ML classifier. This might involve designing and implementing robust data pipelines, optimizing system performance, or maintaining crucial classification infrastructure.