Senior Manager, Machine Learning

See yourself at Twilio

Join the team as Twilio’s next Senior Engineering Manager - Trust Intelligence Platform

About the job

The Traffic Intelligence organization at Twilio establishes trusted communications, ensuring that every interaction is safe, wanted and legal. This position is needed to build advanced machine learning models and robust data pipelines that enable fast, accurate risk predictions and decisions at scale across all communication channels including messaging, voice, email. The engineering team leads systems that are highly scalable and determines if the communications are legal; and wanted in near real time or prior to the communications being sent from the platform. This role requires a blend of technical depth in distributed systems and a strategic mindset to partner with Product and Engineering leaders to execute an AI/ML roadmap.This role interfaces with several key stakeholders and works on initiatives that are tracked at the executive level.

Responsibilities

• Manage and Mentor a team of talented Machine Learning and Data Engineers with various levels of experience and positively influencing their careers.
• Partner with Product Managers and Architects to distill customer needs into actionable technical requirements and long-term roadmaps.
• Ensure best engineering practices & oversee end-to-end execution of large-scale ML solutions with operational excellence.
• Work with data platform teams to build robust, scalable batch and real-time data pipelines.
• Work closely with the Fraud and Compliance Operations team and the Data Analytics team to identify and understand the ever-changing landscape of fraud vectors and then take action to keep up with new forms of fraud.
• Work with other product and development teams to ensure that Twilio’s new and existing products incorporate anti-fraud efforts and publish the appropriate data to our fraud-fighting tools.
• Advocate for agile processes, continuous integration (CI/CD), automated testing, and sophisticated model monitoring to minimize 'toil.'
• Institute and maintain a rotating on-call incident escalation and response processes for the team.
• Manage highly critical risk platform tools in the cloud.
• Own reliability for the team’s services and participate in an on-call rotation.
• Adapt to prioritizing multiple issues in a high-pressure environment.
• Understand complex architectures and be comfortable working with multiple teams.
• Conduct short term and long term planning to achieve team’s goals identifying both tactical and strategic commitments and gaps while performing capacity management and ruthless prioritization.