Machine Learning Engineer

Salary: [Not Specified] Location Type: [Not Specified] Employment Type: [Not Specified]

Who We Are

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.

See Yourself at Twilio

Join the team as Twilio’s next Machine Learning Engineer.

About the Job

This position is needed to build intelligent systems that drive user acquisition, engagement, and retention at scale. You'll work at the intersection of data science, engineering, and marketing, transforming insights into real-time decisions and personalized experiences across our growth engine.

As a Machine Learning Engineer within a Revenue and Growth Marketing department, you will lead, develop, and build data products and advanced machine learning models that support business growth. You will collaborate closely with cross-functional teams to drive business outcomes through data, contributing to strategic objectives.

Responsibilities

In this role, you’ll:

• Design, build, and deploy machine learning models that power growth initiatives, such as customer segmentation, churn prediction, personalization, campaign optimization, and recommendation systems.
• Collaborate with data scientists to translate prototypes into scalable solutions.
• Collaborate with analysts and product managers to turn business questions into measurable ML solutions.
• Evaluate and select appropriate algorithms and models for specific tasks, ensuring scalability and efficiency.
• Develop and maintain data pipelines for model training, validation, and deployment.
• Develop scalable data and ML pipelines using best-in-class tools and practices (e.g., Airflow, Spark, MLflow).
• Conduct model testing, versioning, and documentation to ensure reproducibility and maintainability.
• Integrate ML models into product and marketing systems via APIs or batch/streaming services.
• Monitor model performance in production and implement feedback loops for continuous learning.
• Contribute to experimentation frameworks (e.g., A/B testing infrastructure) to evaluate ML-driven features.
• Ensure best practices in model validation, testing, and performance evaluation.
• Continuously improve existing systems by integrating new data sources and ML techniques.
• Maintain documentation, testing, and governance around models and datasets to ensure reliability and transparency.
• Work closely with stakeholders across various departments (e.g., Marketing, Sales, Product, R&D) to understand business needs and translate them into data science and machine learning solutions.
• Communicate complex technical concepts to non-technical stakeholders clearly and effectively.
• Stay up-to-date with the latest trends and advancements in machine learning and AI, and integrate new techniques into the team's workflow.

Qualifications

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, Machine Learning, Statistics, or related field.
• 2+ years of experience deploying ML models in production environments.
• Proficient in Python and ML libraries such as Scikit-learn.