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Open nowFirst seen 9 hours ago

Senior Software ML Engineer, AI/ML GenAI, Gemini Enterprise

Google3,920 open roles

Where
Sunnyvale, CA, USA
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Your applicationOpen nowSenior Software ML Engineer, AI/ML GenAI, Gemini EnterpriseGoogle · Sunnyvale, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: first seen 9 hours ago

Google median: 29 days open

The posting

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

Minimum qualifications:

  • Bachelor’s degree in Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience in software development with one or more programming languages.
  • 2 years of experience with core Generative Artificial Intelligence (GenAI) technologies (e.g., Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agents) or model training/post-training.
  • 1 year of experience with GenAI concepts such as language modeling or computer vision.

Preferred qualifications:

  • Master’s degree or PhD in Computer Science or a related technical field.
  • Experience in machine learning modeling and tech leadership roles.
  • Proficiency in Python, C++.
  • Experience building production-grade LLM-based applications and working with Google internal infrastructure.
  • Track record of innovation and critical thinking in solving technical problems.

About the job

Google Cloud’s mission is to make every business successful through AI by combining cutting-edge technology, infrastructure, and talent. AI/ML software engineers in Cloud bridge the gap between pioneering models and a massive product vehicle reaching billions. Our talent density and AI-powered tools drive rapid development, rooted in a culture of empowerment and a bias to action. In this role, you aren’t just building technology; you’re shaping the frontier of enterprise and driving the evolution of advanced models.

As a Senior Software/Machine Learning (ML) Engineer in the Gemini Enterprise team, you will be at the heart of the generative Artificial Intelligence (AI) revolution. You won't just be testing models; you will be engineering the systems that define the intelligence, reliability, and helpfulness of Gemini Enterprise for millions of enterprise users. You will architect automated evaluation frameworks, design optimization algorithms, and solve technical issues at the intersection of Large Language Models (LLMs) and enterprise-grade software.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Lead the technical development of agentic features to transform enterprise productivity.
  • 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, and resolve them by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Design and implement Generative Artificial Intelligence (GenAI) solutions, leverage Machine Learning (ML) infrastructure, and evaluate tradeoffs between different techniques and their application domains.
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