Software Engineer, Cloud AI, Early Career

1 Month ago • All levels • Full Stack Development • Backend Development

Job Summary

Job Description

This Software Engineer role at Google's MSCA focuses on implementing and designing Search features, including structured search support, grounding APIs, result reranking, ACL-based filtering, and third-party data integration. It involves Kubernetes-based infrastructure configuration for scalability and performance. Responsibilities include contributing to Search launches, post-GA roadmap items, and solving engineering challenges using advanced GenAI. The role requires working with a small, versatile team, designing, testing, deploying, and maintaining software solutions.
Must have:
  • PhD in relevant field or equivalent experience
  • Software development experience (Python, C, C++, Java, JavaScript)
  • Experience with data structures and algorithms
  • Kubernetes infrastructure configuration
  • Contribution to Search features and post-GA roadmap
Good to have:
  • Experience with distributed systems
  • C++ or Go development experience
  • Kubernetes Controllers, CRDs familiarity
  • Machine Learning and LLM understanding
  • Cloud platform familiarity
  • Python or Java knowledge

Job Details

Minimum qualifications:

  • PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • Experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • Experience working with data structures or algorithms during coursework/projects, research, internships, or practical experience in school or work (e.g., open-source coding).

Preferred qualifications:

  • Experience developing and deploying distributed systems software.
  • Experience developing in C++, Go.
  • Familiarity with Kubernetes development (Kubernetes Controllers, CRDs).
  • Familiarity with Machine Learning and Large Language Model (LLM) concepts.
  • Familiarity with Cloud platforms.
  • Knowledge of Python or Java.

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.

As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

Responsibilities

  • Work on implementation and designs of Search features (e.g., support for structured search, standalone grounding API, reranking of search results based on user's interactions with previous results, filtering out search results based on ACLs, integration with third-party data sources).
  • Work on Kubernetes-based infrastructure configuration, to ensure scalability and performance goals are met.
  • Contribute to launch of Search and to work on future post-GA roadmap items.
  • Contribute to solving novel engineering challenges requiring use of advanced GenAI capabilities.

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