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Staff Software Engineer, Search ML Infrastructure

Google3,070 open roles

Where
Bengaluru, Karnataka, India
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Your applicationOpen nowStaff Software Engineer, Search ML InfrastructureGoogle · Bengaluru, Karnataka, India
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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 30 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: first seen 40 minutes ago

Google median: 30 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • Experience leading technical project strategy, machine learning design, and optimizing machine learning infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • Experience designing, building, and operating large-scale distributed systems, with scalability, fault tolerance, and reliability.
  • Experience in Search and information retrieval.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures and algorithms.
  • 6 years of experience building distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
  • Experience in distributed machine learning and machine learning infrastructure, distributed systems and with machine learning algorithms at scale.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. Join Google Search AI and work at the intersection of industry leading global scale. We apply breakthrough research, leveraging models like Gemini, to launch high-impact products that help billions ask any question and get things done. If you want to drive the future of AI in Search and work with world-class experts to deliver tangible, global impact and continuous innovation, this is the place.

Responsibilities

  • Design, develop, and evolve the major components of our next-generation Search Serving Infrastructure.
  • Own critical areas of the platform to ensure it provides the expected scalability, reliability, and latency of Google Search.
  • Work collaboratively with Associate Team Leads (ATLs), other engineers, (e.g., Team Leads (TLs)), and cross-functional teams to align platform evolution with broader architectural efforts.
  • Lead and mentor junior engineers within the team.
  • Uphold and maintain a high bar for code quality and robustness of production systems.
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