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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.
Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google Deep Mind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.
The Canada base salary range for this full-time position is CAD 216,000-221,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Please note that the compensation details listed in Canada role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Define and communicate team priorities and mid-term technical direction that align with organizational goals, evolving road maps to anticipate future infrastructure and specialized ML requirements.
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Manage individual performance and career growth by setting level-appropriate expectations, providing coaching, and facilitating regular feedback sessions focused on professional development.
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Lead the design and implementation of complex systems and ML infrastructure, writing code to solve problems within the broader technical scope.
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Partner with Product, and UX leadership to define team direction, establish project ownership across global sites, and foster the collaboration between technical leads and partner teams.
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Drive the development, launch, and "landing" of core infrastructure project, ensuring execution and integration across the organization.
Minimum qualifications
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Bachelor's degree or equivalent practical experience.
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8 years of experience in software development.
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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.
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5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
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3 years of experience in a technical leadership role.
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2 years of experience in a people management or team leadership role.
Preferred qualifications
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Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
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3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
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About Google

Google specializes in internet-related services and products, including search, advertising, and software.
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Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
Cons
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Bureaucracy and slow processes
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Online Assessment/Technical Screen
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