Software Engineer, Machine Learning, Payments

About the Role

Google’s software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products must handle information at massive scale and extend well beyond web search. We’re looking for engineers who bring fresh ideas across areas including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design, and mobile.

As a Software Engineer, you will work on a specific project critical to Google’s needs, with opportunities to switch teams and projects as the business evolves. We seek versatile engineers with leadership qualities who are enthusiastic about taking on new problems across the full stack.

The Payments team focuses on making payments simple, seamless, and secure, including consumer payment technologies. The team also powers money movement between Google and its consumers and businesses.

Responsibilities

• Analyze data for statistical insights.
• Develop accurate and fair machine learning models.
• Design experiments and implement new features and metrics.
• Work with product and marketing teams for experimentation and launch.
• Build and maintain production infrastructure, ensuring critical services and data are available and reliable.

Minimum Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages (e.g., Go, Python, C, C++, Java, JavaScript), or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, and debugging).

Preferred Qualifications

• Master’s degree or PhD in Computer Science, or a related technical field.
• Experience developing and maintaining machine learning models in production.
• Knowledge of machine learning techniques and applications.
• Experience analyzing and improving efficiency, scalability, and stability of systems.