Senior Staff Software Engineer, Machine Learning, Cloud AI

Google

full-time

Posted: October 9, 2025

Number of Vacancies: 1

Job Description

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 to 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.

Locations

Sunnyvale, CA, USA

Salary

Salary not disclosed

Skills Required

software developmentadvanced
programming languages (Python, C, C++, Java, JavaScript)advanced
Machine Learning (ML) designadvanced
optimizing ML infrastructureadvanced
software design and architectureintermediate
Large Language Modelsintermediate
NLPintermediate
Generative AIintermediate

Required Qualifications

Bachelor’s degree in computer science, mathematics, applied statistics, machine learning (degree)
8 years of experience with software development in one or more programming languages (experience)
5 years of experience in leading technical project strategy, Machine Learning (ML) design, and optimizing ML infrastructure (experience)
3 years of experience with software design and architecture (experience)
Experience with Large Language Models, NLP, or Generative AI (experience)
Master’s degree or PhD in Engineering, Computer Science, or related field (degree)
5 years of experience working with Large Language Models (experience)
3 years of experience fine-tuning large models (experience)
3 years of experience in a technical leadership role (experience)
3 years of experience applying and productionizing state-of-the-art large visual, language, and multimodal research (experience)
Experience in designing and deploying agentic AI workflows for business process automation (experience)

Responsibilities

Lead the design, implementation, and optimization of machine learning solutions and infrastructure, defining the technical goals and long-term strategy for the product roadmap.
Provide technical leadership by creating demos and proofs-of-concept (POCs), 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 the platform.
Ensure AI/ML quality by reviewing model designs, code, and training data for accuracy, testability, and efficiency.