Software Engineer III, AI/ML, Recommendations, Rankings, Predictions

1 Week ago • 3-5 Years • Artificial Intelligence • $141,000 PA - $202,000 PA

Job Summary

Job Description

Google seeks a Software Engineer III specializing in AI/ML, recommendations, rankings, and predictions. Responsibilities include writing and deploying code for recommendation systems, collaborating on design and code reviews, contributing to documentation, debugging system issues, and optimizing ML models and data processing. The ideal candidate possesses expertise in building and deploying recommendation systems, experience with multimodal ML or LLMs, and a strong background in software development and data structures/algorithms. The role involves working on projects crucial to Google's needs, requiring versatility, leadership, and a willingness to tackle diverse full-stack challenges.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 2+ years experience with data structures/algorithms
  • 1+ year building and deploying recommendation systems
  • Experience with multimodal ML or LLMs
  • Contribute to model optimization and data processing
Good to have:
  • Master's or PhD in Computer Science
  • Experience with accessible technologies
  • Experience developing in C++, Java, or Python
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

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.
  • 2 years of experience with data structures or algorithms.
  • 1 year of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.
  • Experience with multimodal Machine Learning (ML) or LLMs and building and launching ML products.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or in related technical fields.
  • 2 years of experience with software development in one or more programming languages (e.g. C++, Java, Python).
  • Experience developing accessible technologies.

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 US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Write 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.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Build and deploy recommendation systems models, utilize ML infrastructure, and contribute to model optimization and data processing.

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