Senior Manager, Machine Learning

See yourself at Twilio

Join the team as Twilio’s next Senior Engineering Manager - Messaging Risk & Decision 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

In this role, you’ll:

• 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. 

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• 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.

Desired:

• Experience working in fraud/compliance domain.
• Knowledge of telecommunications.
• Familiarity with popular LLMs and latest developments. 

Location

This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA.

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

*Please note the salary range information provided applies only to candidates residing in California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State due to local requirements. Compensation for candidates in other locations will be discussed during the hiring process. Please note that hiring for this role is not restricted to the locations listed above.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $141,520 - 176,900.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $149,840 - $187,300.
• Based in the San Francisco Bay area, California: $166,400 - 208,000.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.

Applications for this role are intended to be accepted until May 21st, 2026, but may change based on business needs.