Software Engineering Manager II, AI/ML Recommendations, Rankings, Predictions, Google Ads - Google

Minimum qualifications:

1. Bachelor’s degree or equivalent practical experience.
2. 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
3. 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
4. 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
5. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

1. Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
2. 3 years of experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects.

As a Software Engineering Manager, you will not only have the technical expertise to lead major projects but also manage a team of Engineers. You will optimize your own code and ensure that Engineers can optimize theirs. You will manage project goals, contribute to product strategy, and help develop your team. Teams work across the company in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, and user interface design.

With your technical and leadership expertise, you will manage engineers across multiple teams and locations, oversee a large product budget, and deploy large-scale projects internationally.

The US base salary range for this full-time position is $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Responsibilities:

1. Set and communicate team priorities that support the broader organization's goals.
2. Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals.
3. Develop the mid-term technical vision and roadmap within the scope of your (often multiple) team(s).
4. Design, guide, and vet systems designs within the scope of the broader area.
5. Lead the design and implementation of recommendation systems, optimize ML infrastructure, and guide the development of model architecture.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.