Engineering Manager, ML Infra, Search
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience in a technical leadership role; overseeing projects and 2 years of experience in a people management, supervision/team leadership role.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in an matrixed organization.
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.
Our mission is to accelerate AI for Search. We do this by providing repeatable, reliable, scalable, and efficient infrastructure platforms to all Search developers, across the machine learning spectrum, from training to serving.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Responsibilities
- Have expertise in Machine Learning (ML) infrastructure and ML Quality, management and leadership experience and strong partnership skills to enact impact leveraging cross-organizational technical collaborations.
- Lead a medium-sized team of engineers to develop ML infrastructure that delivers impactful ML training, serving, and optimization impact to Search. Support team members in skill and career growth.
- Drive technical strategy and roadmaps for infrastructure development and Work with leaders to define and evolve the charter of the area with a balanced portfolio of business priorities and bets.
- Collaborate across multiple teams and functions, driving alignment, prioritization, and execution. Work in a high paced environment. Innovate next directions for infrastructure over quarter time horizons given the rapidly changing technology landscape.
- Exercise judgment to guide sustainable engineering choices for ML systems at scale.
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