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Senior Software Engineer, AI/ML, Search Personalization

Google
California, USA
Senior · 5+ years experience
Onsite
USD 174000-252000 / year
Discovered 5 days ago
jaxpytorchtensorflow

Full Job Posting

Responsibilities

  • Write and test product or system development code.
  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Design and implement recommendation systems models across different domains, leverage ML infrastructure, and contribute to architecture design.
  • Utilize AI tools and technologies; Be prepared to discuss your knowledge and use of AI tools during the hiring process.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, and embedding) in production, and experience building architecture.
  • 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  • 1 year of experience with machine learning frameworks such as TensorFlow, PyTorch, or JAX.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 5 years of experience with data structures and algorithms.
  • Experience developing accessible technologies.
  • Understanding of modern recommendation architectures (e.g., two-tower models, sequential user modeling) and how to integrate large foundation models into existing ranking/retrieval stacks.

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