Senior Software Engineer, Machine Learning, Quantum

3 Months ago • 5-8 Years • Artificial Intelligence • $161,000 PA - $239,000 PA

Job Summary

Job Description

Google is seeking a Senior Software Engineer with expertise in Machine Learning and Quantum computing. Responsibilities include writing and testing code, participating in design reviews, code review, contributing to documentation, and debugging/resolving system issues. The ideal candidate will possess a strong background in software development, machine learning algorithms (TensorFlow), and software design. Experience with accessible technologies is a plus. The role is crucial in advancing Google's quantum computing capabilities and developing solutions for classically intractable problems.
Must have:
  • 5+ years software development experience
  • 3+ years machine learning experience (TensorFlow)
  • 3+ years software testing/launching experience
  • Software design and architecture experience
  • Strong data structures and algorithms knowledge
Good to have:
  • Master's/PhD in Computer Science
  • Technical leadership experience
  • Experience with accessible technologies
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
  • 3 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning or natural language processing.
  • 3 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

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

The full potential of quantum computing will be unlocked with a large-scale computer capable of complex, error-corrected computations. Google Quantum AI's mission is to build this computer and unlock solutions to classically intractable problems. Our roadmap is focused on advancing the capabilities of quantum computing and enabling meaningful applications.

The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 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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