Senior Manager, Machine Learning Remote

At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences.

Our dedication to remote‑first work and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.

The Traffic Intelligence organization at Twilio establishes trusted communications, ensuring that every interaction is safe, wanted and legal. This role 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 and 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 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 and interface with key stakeholders on executive‑level initiatives.

• Manage and mentor a team of Machine Learning and Data Engineers and positively influence their careers.
• Partner with Product Managers and Architects to translate customer needs into actionable technical requirements and long‑term roadmaps.
• Ensure best engineering practices and oversee end‑to‑end execution of large‑scale ML solutions with operational excellence.
• Build robust, scalable batch and real‑time data pipelines with data platform teams.
• Work closely with Fraud and Compliance Operations and Data Analytics to understand evolving fraud vectors and respond to new threats.
• Ensure new and existing products incorporate anti‑fraud efforts and publish appropriate data to fraud‑fighting tools.
• Advocate for agile processes, continuous integration (CI/CD), automated testing, and sophisticated model monitoring to reduce toil.
• Maintain rotating on‑call incident escalation and response processes for the team.
• Manage highly critical risk platform tools in the cloud and own reliability for the team’s services.
• Adapt to prioritising multiple issues in a high‑pressure environment.
• Understand complex architectures and collaborate with multiple teams.
• Plan short‑term and long‑term goals, assess tactical and strategic commitments, and manage capacity.

Required:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 10–14+ years of experience in machine learning / data engineering.
• 5+ years of experience leading and managing engineering teams.
• Proven track record of shipping and maintaining production ML models.
• Experience developing highly available full‑stack applications and distributed systems.
• Stellar communication, organization and management skills in an agile environment.
• Ability to explain technical and business decisions succinctly and in detail.
• Expert proficiency in Python; familiarity with Java or Scala is a plus.
• Deep experience with PyTorch, Tensor Flow or Keras.
• Experience with Kafka, Apache Spark, Hadoop, Presto and Dynamo
  
  DB.
• Significant experience with AWS (specifically Sage Maker, EKS or ECS).
• Familiarity with Datadog, Grafana or similar observability tools.
• Experience in fraud/compliance domain.
• Knowledge of telecommunications.
• Familiarity with popular LLMs and latest developments.

This role is fully remote, except that it is not eligible for hiring in CA, CT, NJ, NY, PA, WA.

Occasional travel may be required for in‑person team or customer meetings.

Competitive pay, generous time‑off, parental and wellness leave, healthcare, retirement savings plan and many other benefits. Offerings vary by location.

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C.:…