Software Engineer III, AI/ML, Search

Socket.dev; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google seeks software engineers to build next-generation technologies that scale for billions of users. You will work across projects spanning information retrieval, distributed systems, AI, NLP, UI, and mobile, with opportunities to switch teams as the company grows.

Individual pay is determined by skills, experience, and education. US compensation ranges from $147,000 to $210,000 with bonus target and equity as part of the package.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of software development experience in one or more languages, or 1 year with advanced degree.
• 1 year of experience in speech/audio, ML, ML infrastructure, or related ML field.
• 1 year of ML infrastructure experience (deployment, evaluation, optimization, data processing).

Responsibilities

• Write product or system development code.
• Collaborate through design and code reviews to ensure best practices.
• Contribute to documentation and educational content for updates.
• Triage issues and debug across hardware, network, or service operations.
• Implement solutions in ML areas, use ML infrastructure, and optimize models.

Skills

Software development

Programming languages

ML infrastructure

Speech/Audio ML

Education

Bachelor's degree

Master's/PhD preferred

Job description

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.
• 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.
• 2 years of experience with data structures and algorithms.
• 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. In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

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.