Software Engineering Manager, Machine Learning Infrastructure, Google Photos

Key Skills

C Programming, C++, Causal inference, Computer Vision (CV), Data pipelines, Data Privacy, Data security, Design, Effective communication skills, Fairness learning, Google Products, GPUs, Image classification, Image processing, Infrastructure as code, Java Programming, JavaScript, Large scale data processing, Leadership, Machine learning techniques, Maintenance, Open Graph APIs, People management, Personalization, Planning and organization, Product Development, Project management, Python Programming, Regulatory Compliance, Social media platforms, Software Development, Supervised learning

Job Description

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 strategic projects, with 2 years of experience in a people management, supervision/team leadership role.
• Experience in Machine Learning Infrastructure.

Preferred qualifications:

• Experience in coaching engineers and developing a leadership bench for Machine Learning engineering teams.
• Experience in leading/managing teams that build scalable media processing systems, model training, and deployment infrastructure, or data collection systems for Machine Learning purposes.
• Experience in any of the following Machine Learning areas: Computer Vision, Image Processing, Image Classification, Data Collection, Data processing, Data Pipelines, or GPUs.
• Familiarity in running large-scale production systems and privacy/security best practices.

About the job

Google Photos is on a mission to be the home for all your memories, automatically organized and brought to life, so you can save and share what matters. To fulfill this mission, Google Photos leverages the latest computer vision and machine learning techniques at scale to power incredible new ways to experience your media library.

As a Software Engineering Manager, you will advance our adoption of Google’s broader Machine Learning platforms, APIs, and industry Machine Learning capabilities. You will help Photos achieve our mission by empowering our feature teams to build new features, you will also help in key infrastructural areas like feature personalization, Machine Learning fairness, regulatory compliance, and platformizing new Machine Learning technologies, all of which are critical to the future of our product.

Google Photos is a photo sharing and storage service developed by Google. Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers. We are dedicated to making Google experiences centered around the user.

The US base salary range for this full-time position is $185,000-$283,000 + 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 for new hire 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. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Set and communicate team priorities that support broader organization's goals. Align strategy, processes, and decision-making across teams.
• Develop and maintain relationships with Google Photos’ product and feature development teams with Google’s broader Research/Core Machine Learning organizations. Enable sustainable Machine Learning features in production.
• Create goals for Machine Learning development within Google Photos that balances platformization of Machine Learning and Computer Vision techniques with system scalability, privacy and regulatory needs, and developer velocity.
• Design, guide, and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems like: standardize our Machine Learning platforms and workflows. Unlock new model training/deployment/inference capabilities.
• Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).