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September 19, 2025

Senior Staff Software Engineer, Machine Learning, Cloud AI

Senior • On-site

$248,000 - $349,000/yr

Sunnyvale, CA

Minimum qualifications:

  • Bachelor’s degree in computer science, mathematics, applied statistics, machine learning, or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience in leading technical project strategy, Machine Learning (ML) design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 3 years of experience with software design and architecture.
  • Experience with Large Language Models, NLP, or Generative AI.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, a technical related field, or equivalent practical experience.
  • 5 years of experience working with Large Language Models.
  • 3 years of experience fine-tuning large models (e.g., supervised, RLHF).
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience applying and productionizing state-of-the-art large visual, language, and multimodal research.
  • Experience in designing and deploying agentic AI workflows for business process automation.

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

As a Senior Staff Machine Learning Engineer, you will develop next-generation AI technologies for our core products such as AI Search, Specialized AI models, and the Developer Platform. You will apply expertise in machine learning, particularly in areas like search, speech, translation, to design and optimize scalable ML models and infrastructure. You will collaborate with technical leads, build AI solutions that help enterprises transform their operations, with a focus on Generative AI and large-scale model optimization.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

The US base salary range for this full-time position is $248,000-$349,000 + 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

  • Lead the design, implementation, and optimization of machine learning solutions and infrastructure, defining the technical goal and long-term strategy for product roadmap.
  • Provide technical leadership by creating demos and proofs-of-concept, managing product briefings, and partnering with product management, DeepMind, and Innovation Labs to drive customer adoption.
  • Architect and develop highly scalable ML systems, including model training pipelines, serving infrastructure, and data processing solutions.
  • Enable client success by working closely with key Google Cloud Platform (GCP) customers to build and deploy enterprise-grade ML offerings on platform.
  • Ensure AI/ML quality by reviewing model designs, code, and training data for accuracy, testability, and efficiency.