Join Twilio as a Staff Machine Learning Engineer
Are you ready to shape the future of communications with cutting-edge AI and data technology? Twilio is hiring a Staff Machine Learning Engineer to design, build, and optimize scalable ML and AI infrastructure that powers global business operations. As a Staff Machine Learning Engineer, you’ll work on advanced data engineering systems supporting teams across Sales, Marketing, and Product—driving automation, data insights, and innovation that redefine how businesses interact with their customers worldwide.
Why the Staff Machine Learning Engineer Role Matters
The Staff Machine Learning Engineer plays a pivotal role in Twilio’s Go-to-Market (GTM) Data Engineering team. You’ll collaborate with data scientists and engineers to develop high-performance data pipelines and ML systems that fuel analytics, automation, and personalization. Your work ensures that massive datasets are efficiently processed, managed, and leveraged for actionable insights that shape Twilio’s business strategy and customer experience.
Key Responsibilities
-
Collaborate with engineers, data scientists, and stakeholders to build world-class data infrastructure.
-
Design and scale infrastructure for managing ML workflows and AI models at enterprise level.
-
Develop high-performance systems for fast and efficient AI agent deployment and serving.
-
Build and manage reverse ETL pipelines to support marketing and sales automation.
-
Improve developer experience through better internal tooling and automation frameworks.
-
Maintain and optimize data warehouses (Snowflake) for accuracy and performance.
-
Create documentation for data pipelines, models, and transformation workflows.
-
Participate in the on-call rotation to ensure data infrastructure reliability and availability.
Qualifications
Required:
-
5+ years of experience in ML platform development or data engineering.
-
Proven track record in delivering large-scale data or ML projects.
-
Deep understanding of infrastructure for ML/AI applications.
-
Hands-on experience with Spark, Flink, or Ray for big data processing.
-
Familiarity with Airflow or Dagster for orchestration.
-
Proficiency in infrastructure-as-code (Terraform) and modern CI/CD pipelines.
Desired:
-
Experience building distributed systems in AWS or similar cloud environments.
-
Skilled in Python, Go, or Java programming.
-
Experience with streaming technologies like Kafka or Kinesis.
Location and Work Environment
This remote Staff Machine Learning Engineer role is open to candidates across the U.S., excluding CA, CT, NJ, NY, PA, and WA. Twilio’s remote-first culture emphasizes flexibility, inclusion, and collaboration. Occasional travel may be required for in-person meetings or project collaborations.
Compensation and Benefits
Twilio offers a competitive compensation package, with salary ranges based on experience and location.
-
Salary range: $152,500 – $224,200 (varies by state).
-
Eligible for Twilio’s equity and bonus programs.
-
Comprehensive benefits: health insurance, 401(k) with match, generous PTO, parental leave, and wellness programs.
About Twilio
Twilio is a global leader in communication technology, empowering businesses and developers to create personalized customer engagement solutions. From SMS and voice APIs to advanced AI and data tools, Twilio helps millions of users connect in meaningful ways. Our mission is to revolutionize how the world communicates—through creativity, collaboration, and innovation.
Why Join Twilio
-
Remote-First Culture: Work from anywhere while staying connected through global collaboration.
-
Innovative Environment: Shape the future of communications with AI, data, and cloud technologies.
-
Career Growth: Access continuous learning, mentorship, and leadership opportunities.
-
Inclusive Community: Thrive in a diverse and supportive workplace driven by “Twilio Magic.”
Equal Opportunity Employer
Twilio is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We also comply with applicable laws regarding fair hiring practices and consider qualified applicants with criminal histories.