Senior Software Engineer, AI/ML, AI Builder

Socket.dev; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google is seeking software engineers to develop next-generation technologies that scale for billions of users. You will work on projects critical to Google’s needs, with opportunities to switch teams as you grow within a fast-paced environment.

Labs focuses on incubating early-stage efforts to advance Google’s mission of organizing the world’s information and making it universally accessible and useful. Individual pay is influenced by skills, experience, and education.

Qualifications

• Bachelor's degree or equivalent practical experience required.
• 5 years of software development experience in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products; 1 year in software design/architecture.
• 3 years of experience with ML infrastructure (deployment, evaluation, data processing, debugging).

Responsibilities

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices.
• Contribute to documentation and adapt content with product updates and user feedback.
• Triage issues and debug/resolve impacts on hardware, network, or services.
• Design and implement solutions in ML areas, leveraging ML infrastructure.

Skills

Software development

Testing & maintenance

ML infrastructure

Software design

Education

Bachelor's degree or equivalent practical experience

Job description

MINIMUM QUALIFICATIONS

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years 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 field.
• 5 years of experience with data structures and algorithms.
• 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.

Labs is a group focused on incubating early-stage efforts in support of Google’s mission to organize the world’s information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Googlehttps://www.google.com/about/careers/applications/benefits/.

RESPONSIBILITIES

• Write and test 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.
• Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.