Software Engineering Manager II, Google Cloud, reCAPTCHA

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.
  
• 2 years of experience building and developing large-scale infrastructure or distributed systems.
  
• 2 years of experience building ML workflows and infrastructure for evaluation or tracking model development.
  
• Applied ML experience to solve real-world problems such as image classification, anomaly detection, ranking, etc.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 3 years of experience working in a complex, 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.

reCAPTCHA Eval team's goal is to make the quality of reCAPTCHA's real-time verdicts measurable and quantifiable, thereby providing accurate and actionable insights.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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. 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

• Drive the development and implementation of robust evaluation strategies to ensure the high quality and effectiveness of our security features.
• Leverage knowledge of anomaly detection techniques to identify and address potential vulnerabilities or unexpected behaviors in reCAPTCHA's Machine Learning (ML) systems.
• Explore and implement innovative synthetic labeling methods, such as label propagation, to enhance the availability of labeled data for training and evaluation.
• Develop and execute a comprehensive evaluation strategy encompassing anomaly detection, quality assessment, and metric selection for reCAPTCHA's ML systems.
  
• Define, track, and analyze key performance indicators to assess the effectiveness and efficiency of models in detecting and mitigating security threats.