Careers
Careers

job details

Back to jobs search

Jobs search results

3,756 jobs matched
Showing 1841 to 1860 of 3756 rows
Back to jobs search

Software Engineer, Search AI Infra Performance

GoogleMountain View, CA, USA

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 machine learning (ML) infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
  • 3 years of experience debugging and optimizing distributed systems.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or a related technical field.
  • 5 years of experience with data structures and algorithms.
  • Experience developing accessible technologies.
  • Experience in working with large language models (LLM).
  • Experience with Search products or infrastructure that uses or is used by generative AI (GenAI) APIs.
  • Experience with LLM tuning, reinforcement learning, supervised fine-tuning, prompt optimization, or other ML 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.

Search artificial intelligence (AI) infrastructure enables the deployment of AI models at Search's scale. We partner with Search AI developers, Google DeepMind, and Core machine learning (ML) to tailor solutions across the ML infrastructure ecosystem.

Our mission is to empower developers with access to Gemini models by optimizing the stack—from orchestration down to the models themselves. We provide the services, tools, and expertise needed for lifecycle management and resource optimization, accelerating AI innovation while eliminating infrastructure overhead for generative AI products.

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 $174,000-$252,000 + 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.

Responsibilities

  • Design tools and processes to streamline developer experience with large language models (LLMs).
  • Ensure models and AI experiences can launch given latency, capacity, and reliability constraints.
  • Ensure use of TPU and other machine learning (ML) accelerators.
  • Drive optimizations across teams and systems for LLMs for latency and throughput across the Search stack.
  • Collaborate with Search ATLs, GDM, CoreML, and Search software engineers (SWEs) and site reliability engineers (SREs).

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.

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 requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.

If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Google apps
Main menu