Software Engineer III, AI/ML, Search at Google

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Feb, 26

Salary

202000.0

Posted On

07 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Development, Machine Learning, Reinforcement Learning, Speech Recognition, Model Deployment, Data Processing, Debugging, Algorithms, Data Structures, Accessible Technologies

Industry

Software Development

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), 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 in 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. The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 benefits at Google [https://careers.google.com/benefits/]. 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.

Responsibilities

Write product or system development code and collaborate with peers and stakeholders through design and code reviews. Implement solutions in specialized ML areas and contribute to model optimization and data processing.