Senior Software Engineering Manager, LearnX

4 Months ago • 8-13 Years • Artificial Intelligence

Job Summary

Job Description

As a Senior Software Engineering Manager at Google's LearnX initiative, you will lead engineering teams in developing AI-driven capabilities for learning products. Responsibilities include building AI features, managing data training systems, and overseeing infrastructure for AI model training. You will define technical goals and strategies, collaborate with stakeholders, and build high-performing engineering teams. This role involves creating cutting-edge AI models to personalize learning experiences, enhancing learning on various Google products, particularly in STEM education. The aim is to make learning more accessible and effective for everyone through tailored explanations and interactive simulations.
Must have:
  • 8+ years software development experience
  • 5+ years technical leadership
  • 5+ years people management
  • AI model development expertise
  • Lead engineering teams
  • Manage data training systems
Good to have:
  • Master's or PhD in CS
  • Experience with backend data infrastructure
  • Experience coaching engineers
  • Experience with ideation and innovation at scale

Job Details

Minimum qualifications:

  • Bachelor’s degree, or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or in a related technical field.
  • Experience in Machine Learning (ML), building /training Artificial Intelligence (AI) models, backend data infrastructure or data engineering.
  • Experience in managing Software Engineering teams and delivering multi-quarter projects.
  • Experience with coaching and supporting engineers and engineering managers.
  • Experience with ideation and innovating at scale.
  • Ability to collaborate with other people, teams, function across the world and communicate cross-functionally.

About the job

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

In this role, you will develop cutting-edge Artificial Intelligence (AI) models that personalize learning experiences and provide learners with the information they need, when they need it. You will collaborate across Google to enhance learning on different products, especially in Science, Technology, Engineering, and Math (STEM) education. Learners will search for a math concept and instantly receiving tailored explanations, or use Google Lens to identify a machine and access interactive simulations. By combining AI expertise with educational understanding, you will make learning more accessible, engaging, and effective for everyone.

Responsibilities

  • Lead Engineering teams, build Artificial Intelligence (AI) driven capabilities and features for learning products. 
  • Guide the development of AI capabilities and features, manage data training systems, and oversee infrastructure for efficient AI model training. 
  • Define technical goal, strategy, and roadmap.
  • Collaborate with stakeholders to drive project delivery.
  • Build and manage a high-performing Engineering team.

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