Senior Manager, Machine Learning

Role Overview

• 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.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 10–14+ years of total experience in machine learning /data engineering.
• 5+ years of experience leading and managing engineering teams.
• Proven track record of shipping and maintaining ML models in a fast-paced, production environment.
• Experience developing highly-available full stack applications and distributed systems
• Stellar communication, organization and management skills with proven track record in an agile environment.
• Ability to explain your technical and business decisions succinctly as well as in detail.
• Languages: Expert proficiency in Python. Familiarity with Java or Scala is a plus.
• ML Frameworks: Deep experience with PyTorch, TensorFlow, or Keras.
• Data Tools: Experience with Kafka, Apache Spark, Hadoop, Presto, and DynamoDB.
• Cloud Platforms: Significant experience with AWS (specifically SageMaker, EKS, or ECS).
• Observability: Familiarity with tools like Datadog and Grafana.

Tech Stack

• Apache
• AWS
• Cloud
• Distributed Systems
• DynamoDB
• Grafana
• Hadoop
• Java
• Kafka
• Keras
• Python
• PyTorch
• Scala
• Spark
• Tensorflow

Benefits

• Health care insurance
• 401(k) retirement account
• Paid sick time
• Paid personal time off
• Paid parental leave