Software Engineering Manager, ML
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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).
- 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
Preferred qualifications:
- Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- 3 years of experience in developing machine learning models in areas such as recommender systems, pricing optimization, user modeling, or computational advertising.
- Experience architecting and launching ML systems that operate at scale.
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
- Define and drive the long-term technical direction and strategy for ML-powered personalization, pricing, and recommendation systems.
- Collaborate with Product Managers and other engineering leaders to translate business needs into technical solutions and influence the product road map.
- Architect, build, and scale production-grade ML systems with an emphasis on performance, reliability, debuggability, and model explainability.
- Lead a team of Engineers, act as a technical pillar for the team and mentor the engineers, fostering their growth, providing design guidance, and cultivating a culture of engineering excellence.
- Identify and advocate new, high-impact applications of machine learning to drive user growth, engagement, and business growth for Google One and its partner products.
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