Machine Learning Engineer

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, TensorFlow, PyTorch, or LightGBM and tools for model deployment (e.g., MLflow, Kubernetes, Docker, Metaflow)..
• Experience with data pipeline tools (e.g., Airflow, dbt) and big data processing (e.g., Spark, Presto).
• Familiarity with cloud-based ML platforms (e.g., AWS SageMaker, Google Vertex AI).
• Proficient in programming languages such as Python, R, or Java.
• Solid understanding of statistical methods, machine learning algorithms, and deep learning techniques.
• Proven experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, GCP, Azure).
• Strong understanding of experimentation design and metrics relevant to growth (e.g., conversion rate, LTV).
• Comfortable working in a fast-paced, collaborative environment focused on measurable impact.

Desired:

• Experience with user behavior modeling, marketing attribution, or real-time decision systems.
• Understanding of MLOps practices, including CI/CD for ML, model monitoring, and retraining pipelines.
• Familiarity with communication channels and platforms (e.g., push, email, in-app messaging).

Location

This role will be remote, and based in Ontario.

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

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

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