Software Engineer III, AI/ML, Google Research

3 Months ago • 2 Years + • Research & Development

Job Summary

Job Description

Google Research seeks a Software Engineer III specializing in AI/ML. Responsibilities involve writing product/system development code, collaborating on design and code reviews, contributing to documentation, debugging and resolving system issues, implementing solutions in specialized ML areas, utilizing ML infrastructure, and optimizing models and data processing. The ideal candidate will have a strong background in software development, data structures/algorithms, and experience with at least one ML area (speech/audio, reinforcement learning, ML infrastructure). This role demands collaboration, problem-solving skills, and a commitment to pushing technological boundaries.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 2+ years experience with data structures/algorithms
  • 1+ year experience in ML (speech, RL, infrastructure)
  • 1+ year experience with ML infrastructure (deployment, evaluation, etc.)
  • Strong coding skills
  • Collaboration and problem-solving abilities
Good to have:
  • Master's or PhD in CS or related field
  • Experience with accessible technologies

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 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).

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 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.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

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.
  • Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

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