📍 Job Overview

Job Title: Software Engineer III, AI/ML GenAI, Google Cloud AI
Company: Google
Location: Sunnyvale, California, United States
Job Type: On-site
Category: AI/ML Engineer
Date Posted: June 30, 2025
Experience Level: 2-5 years

🚀 Role Summary

Develop and implement cutting-edge GenAI solutions for Google Cloud AI, focusing on text, image, video, or audio generation.
Collaborate with cross-functional teams to maximize scientific and real-world impact, pushing the state-of-the-art in AI and sharing findings with the broader research community.
Work on unique AI challenges motivated by Google Cloud's mission to bring AI to various industries, such as tech, healthcare, finance, and retail.
Contribute to real-world impact by collaborating with product teams to bring innovations to customers.

📝 Enhancement Note: This role requires a strong background in GenAI concepts and ML infrastructure, as well as experience with data structures and algorithms. Familiarity with accessible technologies is a plus.

💻 Primary Responsibilities

Code Development: Write product or system development code, ensuring best practices and efficient solutions.
Collaboration: Work with peers and stakeholders through design and code reviews to ensure high-quality, maintainable, and performant code.
Documentation: Contribute to existing documentation or educational content, adapting it based on product updates and user feedback.
Issue Triage: Triage and resolve product or system issues by analyzing their sources and impacts on hardware, network, or service operations and quality.
AI Solution Implementation: Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

📝 Enhancement Note: This role involves a significant amount of coding and collaboration, requiring strong problem-solving skills and the ability to work effectively in a team environment.

🎓 Skills & Qualifications

Education: A Bachelor's degree or equivalent practical experience is required. A Master's degree or PhD in Computer Science or related technical fields is preferred.

Experience: At least 2 years of experience with software development in one or more programming languages is required. Experience with GenAI concepts, ML infrastructure, and data structures or algorithms is also required.

Required Skills:

Proficiency in one or more programming languages
Strong understanding of GenAI concepts (LLM, Multi-Modal, Large Vision Models)
Experience with ML infrastructure (model deployment, model evaluation, optimization, data processing, debugging)
Familiarity with data structures and algorithms

Preferred Skills:

Experience with accessible technologies
Familiarity with Google Cloud AI products and services

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate your proficiency in GenAI concepts and ML infrastructure through relevant projects and case studies.
Showcase your problem-solving skills and ability to implement efficient solutions.
Highlight your collaboration skills and experience working with cross-functional teams.

Technical Documentation:

Provide clear and concise documentation of your projects, including code comments, version control, and deployment processes.
Include testing methodologies, performance metrics, and optimization techniques used in your projects.

📝 Enhancement Note: As this role focuses on AI/ML, your portfolio should emphasize your technical skills and problem-solving abilities in the context of GenAI and ML infrastructure.

💵 Compensation & Benefits

Salary Range: The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Benefits:

Bonus
Equity
Benefits

Working Hours: This role follows a standard 40-hour workweek, with flexibility for project deadlines and maintenance windows.

📝 Enhancement Note: The provided salary range is determined by Google's internal salary ranges and may vary based on the candidate's location, skills, and experience.

🎯 Team & Company Context

🏢 Company Culture

Industry: Google operates in the technology industry, with a strong focus on AI, machine learning, and cloud services. This role will allow you to work on cutting-edge AI/ML projects that have real-world impact across various industries.

Company Size: Google is a large company with a global presence, employing over 135,000 people worldwide. This size provides ample opportunities for collaboration, growth, and exposure to diverse projects and teams.

Founded: Google was founded in 1998 and has since grown into one of the world's leading technology companies, known for its innovative products and services, including search, advertising, and cloud computing.

Team Structure:

The Google Cloud AI team consists of researchers, engineers, and product managers working together to advance AI technologies and bring them to customers.
The team is organized into smaller groups focused on specific research areas and projects.

Development Methodology:

Google follows Agile development methodologies, with a focus on collaboration, iteration, and continuous improvement.
The team uses code reviews, testing, and quality assurance practices to ensure high-quality, maintainable code.

Company Website: Google

📝 Enhancement Note: Google's company culture emphasizes innovation, collaboration, and user focus. This role will allow you to work on impactful AI/ML projects that benefit various industries and users worldwide.

📈 Career & Growth Analysis

AI/ML Engineer Career Level: This role is at the intermediate level, requiring a solid foundation in AI/ML concepts and experience implementing GenAI solutions. The role offers opportunities for growth in technical leadership, architecture decisions, and specialization in specific AI/ML domains.

Reporting Structure: This role reports directly to the Google Cloud AI team, collaborating with researchers, engineers, and product managers to advance AI technologies and bring them to customers.

Technical Impact: As an AI/ML Engineer, you will have a significant impact on Google Cloud AI products and services, contributing to real-world impact across various industries, such as tech, healthcare, finance, and retail.

Growth Opportunities:

Technical Growth: Deepen your expertise in AI/ML, specializing in specific domains or technologies, and contribute to cutting-edge research projects.
Leadership Growth: Develop your leadership skills by mentoring junior engineers, driving projects, and making critical architecture decisions.
Product Growth: Collaborate with product teams to bring AI/ML innovations to customers, gaining insights into product development and customer needs.

📝 Enhancement Note: This role offers numerous growth opportunities, allowing you to advance your technical skills, leadership abilities, and product understanding in the AI/ML domain.

🌐 Work Environment

Office Type: Google's Sunnyvale office is a modern, collaborative workspace designed to foster innovation and creativity. The office features open-plan workspaces, meeting rooms, and recreational areas, promoting interaction and collaboration among team members.

Office Location(s): Sunnyvale, California, United States

Workspace Context:

Collaboration: The office encourages cross-functional collaboration, with open workspaces and dedicated areas for team meetings and brainstorming sessions.
Tools & Equipment: Google provides state-of-the-art development tools, multiple monitors, and testing devices to ensure engineers have the resources they need to succeed.
Interaction: The office fosters interaction among team members, with regular team-building activities, social events, and on-site amenities, such as cafes and fitness centers.

Work Schedule: This role follows a standard 40-hour workweek, with flexibility for deployment windows, maintenance, and project deadlines. Google encourages work-life balance and offers flexible working arrangements to accommodate individual needs.

📝 Enhancement Note: Google's work environment is designed to support collaboration, innovation, and work-life balance, providing the resources and support necessary for engineers to succeed in their roles.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: Demonstrate your proficiency in GenAI concepts and ML infrastructure through coding challenges and problem-solving exercises.
System Design: Showcase your ability to design and implement scalable AI/ML systems, considering performance, efficiency, and user experience.
Behavioral Questions: Discuss your problem-solving approach, collaboration skills, and adaptability in a dynamic work environment.
Final Evaluation: Present your portfolio, highlighting your technical skills, problem-solving abilities, and collaboration experiences.

Portfolio Review Tips:

Project Selection: Choose projects that demonstrate your proficiency in GenAI concepts and ML infrastructure, focusing on text, image, video, or audio generation.
Case Studies: Prepare case studies that highlight your problem-solving skills, collaboration experiences, and the real-world impact of your projects.
Code Quality: Ensure your code is well-documented, efficient, and follows best practices for maintainability and performance.

Technical Challenge Preparation:

Practice Coding: Brush up on your coding skills, focusing on data structures, algorithms, and problem-solving techniques relevant to AI/ML.
System Design: Study system design principles and patterns, focusing on scalability, performance, and user experience.
Communication: Prepare clear and concise explanations of your technical approach, architecture decisions, and problem-solving strategies.

ATS Keywords: (Organized by category)

Programming Languages: Python, TensorFlow, PyTorch, Keras
AI/ML Frameworks: Scikit-learn, XGBoost, LightGBM, CatBoost
ML Infrastructure: MLflow, TensorBoard, Kubeflow, AWS SageMaker, GCP AI Platform
Tools: Jupyter Notebooks, Git, Docker, Kubernetes, Cloud platforms (AWS, GCP, Azure)
Soft Skills: Problem-solving, collaboration, communication, adaptability, innovation
Industry Terms: GenAI, LLM, Multi-Modal, Large Vision Models, ML infrastructure, data processing, optimization, debugging

📝 Enhancement Note: The interview process for this role will focus on your technical skills, problem-solving abilities, and collaboration experiences in the context of AI/ML and GenAI concepts.

🛠 Technology Stack & Web Infrastructure

AI/ML Technologies:

GenAI: LLM, Multi-Modal, Large Vision Models
ML Infrastructure: Model deployment, model evaluation, optimization, data processing, debugging
Programming Languages: Python, TensorFlow, PyTorch, Keras

AI/ML Tools & Frameworks:

ML Libraries: Scikit-learn, XGBoost, LightGBM, CatBoost
ML Workflow Tools: MLflow, TensorBoard, Kubeflow, AWS SageMaker, GCP AI Platform

Development & DevOps Tools:

Version Control: Git
Containerization: Docker
Orchestration: Kubernetes
Cloud Platforms: AWS, GCP, Azure

📝 Enhancement Note: This role requires a strong background in AI/ML technologies, with a focus on GenAI concepts and ML infrastructure. Familiarity with relevant programming languages, tools, and frameworks is essential for success in this role.

👥 Team Culture & Values

AI/ML Team Values:

Innovation: Emphasize cutting-edge research, pushing the boundaries of AI/ML, and driving real-world impact.
Collaboration: Foster a culture of collaboration, knowledge sharing, and continuous learning among team members.
User Focus: Prioritize user needs and experiences, ensuring AI/ML solutions are accessible, intuitive, and beneficial to customers.
Quality: Maintain high standards for code quality, performance, and maintainability, ensuring AI/ML solutions are reliable and scalable.

Collaboration Style:

Cross-Functional Collaboration: Work closely with researchers, engineers, and product managers to advance AI/ML technologies and bring them to customers.
Code Review Culture: Participate in code reviews to ensure high-quality, maintainable, and performant code.
Peer Programming: Collaborate with team members on coding tasks, sharing knowledge, and improving collective skills.

📝 Enhancement Note: Google's AI/ML team values innovation, collaboration, user focus, and quality, fostering a culture of continuous learning and improvement in the AI/ML domain.

⚡ Challenges & Growth Opportunities

Technical Challenges:

GenAI Complexity: Develop and implement complex GenAI solutions, considering text, image, video, or audio generation and the unique challenges associated with each modality.
ML Infrastructure: Optimize ML infrastructure for performance, efficiency, and scalability, ensuring AI/ML solutions can be deployed and maintained at scale.
Data Processing: Design and implement efficient data processing pipelines, considering data cleaning, transformation, and feature engineering to support AI/ML models.
Real-World Impact: Collaborate with product teams to bring AI/ML innovations to customers, ensuring they address real-world challenges and deliver tangible benefits.

Learning & Development Opportunities:

Technical Skills: Deepen your expertise in AI/ML, specializing in specific domains or technologies, and contribute to cutting-edge research projects.
Leadership Skills: Develop your leadership skills by mentoring junior engineers, driving projects, and making critical architecture decisions.
Product Understanding: Collaborate with product teams to bring AI/ML innovations to customers, gaining insights into product development and customer needs.

📝 Enhancement Note: This role presents numerous technical challenges and growth opportunities, allowing you to advance your skills in AI/ML, leadership, and product understanding in the context of real-world impact.

💡 Interview Preparation

Technical Questions:

GenAI Concepts: Demonstrate your understanding of GenAI concepts, such as LLM, Multi-Modal, and Large Vision Models, and their applications in text, image, video, or audio generation.
ML Infrastructure: Explain your experience with ML infrastructure, including model deployment, model evaluation, optimization, data processing, and debugging.
System Design: Discuss your approach to designing and implementing scalable AI/ML systems, considering performance, efficiency, and user experience.

Company & Culture Questions:

AI/ML Innovation: Describe your experience with cutting-edge AI/ML research and how you have driven real-world impact through your projects.
Collaboration: Share examples of your collaboration experiences, highlighting your ability to work effectively in a team environment and drive collective success.
User Focus: Explain your approach to ensuring AI/ML solutions are accessible, intuitive, and beneficial to users, considering their needs and preferences in your design and implementation decisions.

Portfolio Presentation Strategy:

Project Selection: Choose projects that demonstrate your proficiency in AI/ML, focusing on GenAI concepts, ML infrastructure, and real-world impact.
Case Studies: Prepare case studies that highlight your problem-solving skills, collaboration experiences, and the tangible benefits of your projects.
Code Walkthrough: Provide a clear and concise walkthrough of your code, explaining your technical approach, architecture decisions, and optimization techniques.

📝 Enhancement Note: The interview process for this role will focus on your technical skills, problem-solving abilities, and collaboration experiences in the context of AI/ML and GenAI concepts. Be prepared to discuss your approach to technical challenges, system design, and real-world impact.

📌 Application Steps

To apply for this AI/ML Engineer role at Google:

Customize Your Portfolio: Tailor your portfolio to highlight your proficiency in AI/ML, focusing on GenAI concepts, ML infrastructure, and real-world impact.
Optimize Your Resume: Highlight your technical skills, problem-solving abilities, and collaboration experiences in the context of AI/ML and GenAI concepts.
Prepare for Technical Challenges: Brush up on your coding skills, study system design principles, and practice explaining your technical approach and problem-solving strategies.
Research Google: Familiarize yourself with Google's products, services, and company culture, focusing on AI/ML and its real-world impact across various industries.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and AI/ML industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Software Engineer III, AI/ML GenAI, Google Cloud AI