Software Engineer III, Machine Learning, Google Research

10 Months ago • 2-4 Years
Research Development

Job Description

As a Software Engineer III, Machine Learning at Google Research, you'll work on cutting-edge technologies that impact billions of users. You'll contribute to projects critical to Google's needs, collaborating with a team of talented engineers. This role offers opportunities to switch teams and projects as you grow and evolve. You'll manage project priorities, deadlines, and deliverables. Your responsibilities will include designing, developing, testing, deploying, maintaining, and enhancing software solutions. You'll be involved in design reviews, code reviews, and resolving product or system issues. You'll also contribute to documentation and educational content. Google Research is dedicated to addressing the challenges that define the technology of today and tomorrow, making discoveries that impact everyone, and sharing research and tools to fuel progress in the field.
Good To Have:
  • Master's degree or PhD in Computer Science or related technical field
  • Experience developing accessible technologies
Must Have:
  • Bachelor's degree or equivalent practical experience
  • 2 years of experience with software development
  • 2 years of experience with data structures or algorithms
  • 2 years of experience with machine learning algorithms and tools

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

tensorflow
algorithms
deep-learning
data-structures
networking

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 in either an academic or industry setting.
  • 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.

Preferred qualifications:

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