Staff Software Engineer, Content Safety, Productionization

Google Google · Big Tech · Singapore

Staff Software Engineer at Google focused on Content Safety, Productionization. This role involves safeguarding business-critical products, including GenAI experiences, by designing, building, and scaling content safety solutions like classifiers and multimodal understanding. Key responsibilities include working on agentic workflows for threat understanding and content moderation, leading ML solution design, optimizing ML infrastructure, and guiding model optimization and data processing strategies. The role requires significant experience in software development, ML infrastructure, and ML design, with a focus on productionizing AI for safety.

What you'd actually do

  1. Safeguard business-critical products that represent business growth, market share or value to Google, including Generative Artificial Intelligence (GenAI)-based server-side and on-device experiences.
  2. Design, build, maintain and scale content safety solutions (e.g., classifiers, multimodal understanding) to make quality users experience.
  3. Work on projects such as agentic workflows for threat understanding and content moderation.
  4. Lead the design and implementation of solutions in specialized Machine Learning (ML) areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

Skills

Required

  • software development
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • ML design
  • model deployment
  • model evaluation
  • data processing
  • debugging
  • fine tuning
  • testing
  • launching software products
  • software design
  • software architecture

Nice to have

  • technical leadership
  • leading project teams
  • setting technical direction
  • content safety
  • responsible AI
  • factuality
  • product policy
  • scaling pipelines
  • deploying systems
  • defensive architecture
  • Service Level Objectives (SLOs)
  • machine learning
  • Large Language Models (LLMs)
  • transformers
  • activations
  • training LLMs
  • deploying LLMs

What the JD emphasized

  • 8 years of experience in software development
  • 5 years 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 a related ML field.
  • 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 5 years of experience with testing, and launching software products, and 3 years of experience with software design and architecture.

Other signals

  • Safeguard business-critical products
  • Design, build, maintain and scale content safety solutions
  • Work on projects such as agentic workflows for threat understanding and content moderation
  • Lead the design and implementation of solutions in specialized Machine Learning (ML) areas
  • optimize ML infrastructure
  • guide the development of model optimization and data processing strategies