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Salary
≈ $162k – $312k per year (Estimated)
Location
In office (Mountain View)
Seniority
Middle · 2+ years exp

Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Oct 30, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

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.

Labs is a group focused on incubating early-stage efforts in support of Google’s mission to organize the world’s information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes.

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

  • Apply deep expertise in agentic systems including planning, memory, context management, tool-use, and loops to rapidly prototype and evaluate novel solutions for user simulation, playtesting and making software testable.
  • Exercise strong product judgment to build "right-sized," reliable infrastructure for agent serving-prioritizing velocity and MVP readiness while maintaining practical standards for latency, quality, and cost.
  • Design benchmarks to measure success and perform quality work for the agentic stack, and constantly analyze, iterate and pivot with fast experiments.
  • Operate with a rolled-up mindset by seamlessly blending the responsibilities of Software Engineering, Product Management, Research, Data Science and UX Research teams.
  • Thrive in a fast-moving, 0-to-1 space. Turn open-ended product and technical questions into clear implementations, working closely with an agile team to test ideas and build solutions.

Qualifications

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), ML infrastructure, or specialization in another ML field.
  • 1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or in a related technical field.
  • 2 years of experience with data structures and algorithms.
  • Experience developing accessible technologies.
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