Software Engineer, Search, AI​/ML Training Infrastructure

Software Engineer, Search, AI/ML Training Infrastructure

Google place Mountain View, CA, USA

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• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, Machine Learning, Large Scale Distributed Systems, Large Language Model 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).

• Master's degree or PhD in Computer Science or related technical fields.
• 2 years of experience with data structures or algorithms.
• 1 year of experience with Recommender Systems, Data Analysis, Streaming, Machine Learning Infrastructure.

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.

Our team mission is to accelerate AI innovation for the discover feed by providing a data and training foundation. Our current technical focus areas include:
Next level training capability, including real-time training, co-training ranking and retrieval models. User sequence modeling data quality and efficiency, apply the latest research to improve model quality and reduce computational cost. Scale up Large Language Model (LLM) based users and content understanding. Data availability, innovate on data ingestion and storage to achieve better availability, and coverage for model training and serving.

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 .

• Design, implement, deploy and maintain various projects. Collaborate with peer team members (ranking, retrieval) for understanding various needs and system limitations in order to make informed decisions.
• 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.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal…