Software Engineer III, AI/ML, Platforms and Devices

Socket.dev; Seattle (WA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google's Platforms and Devices team develops software platforms across desktop and mobile, and integrates first-party devices and services with Google AI, software, and hardware. Engineers work on projects spanning information retrieval, large-scale systems, AI, NLP, and mobile tech to push technology forward.

Individual pay is determined by skills, experience, and education. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year with ML: speech/audio, RL, ML infrastructure or related ML field.
• 1 year with ML infrastructure: model deployment, evaluation, optimization, data processing, debugging.

Responsibilities

• Write product or system development code.
• Collaborate with peers through design and code reviews to ensure best practices.
• Contribute to existing documentation and adapt content based on updates and feedback.
• Triage issues and debug/resolve affecting hardware, network, or service operations.
• Implement solutions in specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Skills

Python

C++

ML infra

Speech/Audio ML

Reinforcement learning

Education

Bachelor's degree or equivalent practical experience

Master's/PhD in CS or related field

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 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 or algorithms.
• Experience developing accessible technologies.
• Experience with Android development.
• Experience with Natural Language Processing (NLP) concepts or techniques.

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 Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

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.