Engineering Manager, CodeAI Foundations
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
- Experience with machine learning infrastructure.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- Experience building, scaling, and productionizing AI/ML solutions.
- Experience with technical leadership in the AI/ML space.
- Experience as an applied ML engineer.
- Experience with Google's AI infrastructure, agent infra, and building scalable systems.
- Passion for machine learning, data analysis, and developer tools.
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.
Responsibilities
- Own the technical goal and end-to-end architecture for Artificial Intelligence solutions, and help shape the direction for next-generation Artificial Intelligence efforts.
- Drive efforts from initial ideation, experimentation, and prototyping to build robust, scalable production systems, including close collaboration with partners for integration.
- Lead the team in building necessary evaluations and infrastructure to deliver high-quality solutions, driving end-to-end quality and development for new Critical User Journeys, and analyzing experiments.
- Build, mentor, and scale the team of engineers, promoting a culture of excellence, rapid prototyping, and high-quality execution.
- Partner with the product team and stakeholders to convert Critical User Journeys into concrete technical requirements, and build collaborations across partner teams to deliver on high-impact solutions.
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