Software Engineer II, Full Stack, Core

5 Months ago • 1 Years +
Full Stack Development

Job Description

As a Software Engineer II, Full Stack, Core at Google, you'll contribute to the technical foundation of Google's flagship products. Responsibilities include identifying data sources and designing signals to detect threats, optimizing signal generation processes, analyzing and enhancing machine learning models for abuse prevention, and building knowledge in emerging abuse trends. You'll work across the full stack, using languages like Java, Python, Go, C++, JavaScript, TypeScript, HTML, and CSS. The role involves developing and deploying machine learning models and requires experience with data structures, algorithms, and full-stack development. You will be part of the Core team, impacting important technical decisions across the company.
Good To Have:
  • Experience in adversarial space, fraud detection, or anti-abuse domains
  • Experience developing and deploying machine learning models
  • Deep learning or natural language processing experience
Must Have:
  • Bachelor's degree or equivalent experience
  • 1+ year software development experience (Python, C, C++, Java, JavaScript)
  • 1+ year experience with data structures/algorithms
  • 1+ year full-stack development experience
  • Threat detection and protection strategy

Add these skills to join the top 1% applicants for this job

java
javascript
python
html
css
typescript
algorithms
back-end
deep-learning
data-structures
front-end
foundation
scalability
innovation
networking

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 1 year of experience with data structures or algorithms.
  • 1 year of experience with full stack development, across back-end such as Java, Python, GO, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.

Preferred qualifications:

  • Experience in the adversarial space, fraud detection, or other anti-abuse domains.
  • Experience developing and deploying machine learning models, deep learning or natural language processing techniques.

About the job

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 need to handle information at massive scale, and extend well beyond web search. 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’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. 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.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

Responsibilities

  • Identify data sources and design signals to detect threats, contributing to the formulation of enhanced protection strategies.
  • Optimize signal generation processes, including identifying and resolving performance issues to ensure scalability.
  • Analyze and enhance machine learning models for abuse prevention and detection.
  • Build knowledge in emerging abuse trends, designing, implementing, and testing innovative strategies.

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