Senior Software Engineer, Machine Learning, Google Research

9 Months ago • 4-8 Years
Research Development

Job Description

As a Senior Software Engineer in Google Research's Machine Learning team, you'll design, develop, test, deploy, maintain, and enhance software solutions for critical Google projects. Responsibilities include writing and testing code, participating in design reviews, reviewing code from peers, contributing to documentation, troubleshooting issues, and analyzing their impact. You will work with ML/AI algorithms, deep learning, and natural language processing. The role demands expertise in software development, data structures, algorithms, and experience in launching software products. Leadership qualities and versatility are crucial for success in this fast-paced environment.
Good To Have:
  • Master's or PhD in Computer Science
  • Technical leadership experience
  • Experience developing accessible technologies
Must Have:
  • Bachelor's degree or equivalent experience
  • Software development experience
  • Data structures/algorithms knowledge
  • ML/AI algorithms and tools experience
  • Testing and launching software products
  • Software design and architecture experience

Add these skills to join the top 1% applicants for this job

algorithms
deep-learning
data-structures
networking
user-interface

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • Experience with software development in one or more programming languages, and with data structures/algorithms.
  • Experience testing, maintaining and/or launching software products, and with software design and architecture.
  • Experience with ML/AI algorithms and tools, deep learning and/or natural language processing.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience in a technical leadership role.
  • 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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

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 and test product or system development code.
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Review code developed by other developers and provide feedback to ensure best practices (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.

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