Senior Software Engineer, AI Innovation and Res... @ Google
Your Application Journey
Email Hiring Manager
Job Details
Minimum Qualifications
Bachelor’s degree or equivalent practical experience. 5 years of experience in software development with one or more programming languages and a strong understanding of data structures/algorithms. Additionally, 3 years of experience in testing, maintaining, or launching software products, with at least 1 year in software design and architecture. Also required is 3 years of experience with Machine Learning (ML) infrastructure, including model deployment, model evaluation, data processing, and debugging.
Preferred Qualifications
- Experience in technical projects from conception to deployment.
- Experience in a research or academic setting translating research to practical applications.
- Expertise in machine learning, deep learning, and AI development with production-level model deployment.
- Understanding of Partner and Devices product portfolio and AI integration.
- Ability to work with distributed teams across multiple time zones.
About the Job
At Google, our software engineers develop next-generation technologies that change how billions of users interact with information. As a Senior Software Engineer, you will work on critical projects with opportunities to switch teams as business needs evolve. Your role will involve designing, developing, testing, deploying, maintaining, and enhancing software solutions on a massive scale.
Team Overview
The Platforms and Devices team covers Google's various computing software platforms including desktop, mobile, and applications, alongside first-party devices and services that integrate Google AI with hardware and software. This team collaborates closely with product and research teams to build innovative user experiences globally.
Responsibilities
- Develop, train, evaluate, and deploy AI/ML models ensuring robustness and scalability.
- Collaborate with Partners and Devices Forum product and research teams for AI-based features.
- Work within a collaborative team to maximize efficiency and impact.
- Build shared infrastructure and blueprints to accelerate future engagements.
- Transfer valuable AI knowledge to empower product teams for future initiatives.
Key skills/competency
- AI
- Machine Learning
- Software Development
- Distributed Systems
- System Design
- Research
- Model Deployment
- ML Infrastructure
- Full-Stack
- Production-Ready
How to Get Hired at Google
🎯 Tips for Getting Hired
- Research Google's culture: Understand company values and mission.
- Customize your resume: Highlight AI and full-stack expertise.
- Network: Connect with current engineers on LinkedIn.
- Prepare for interviews: Focus on technical and system design questions.