Original listing text, shown exactly as published by the company.
Responsibilities
In this role, you’ll
- Architect, implement, and maintain scalable data pipelines and feature stores for batch and real-time workloads.
- Build reproducible ML training, evaluation, and inference workflows using modern orchestration and MLOps tooling.
- Integrate event streams from Twilio products (e.g., Messaging, Voice, Segment) into unified, analytics-ready datasets.
- Monitor, test, and improve data quality, model performance, latency, and cost.
- Partner with product, data science, and security teams to ship resilient, compliant services.
- Automate deployment with CI/CD, infrastructure-as-code, and container orchestration best practices.
- Produce clear documentation, dashboards, and runbooks; share knowledge through code reviews and brown-bag sessions.
- Embrace Twilio’s “We are Builders” values by taking ownership of problems and driving them to completion.
Qualifications
Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to 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
- B.S. in Computer Science, Data Engineering, Electrical Engineering, Mathematics, or related field—or equivalent practical experience.
- 4-8 years building and operating data or ML systems in production.
- Proficient in Python and SQL; comfortable with software engineering fundamentals (testing, version control, code reviews).
- Hands-on experience with ETL/ELT orchestration tools (e.g., Airflow, Dagster) and cloud data warehouses (Snowflake, BigQuery, or Redshift).
- Familiarity with ML lifecycle tooling such as MLflow, SageMaker, Vertex AI, or similar.
- Working knowledge of Docker and Kubernetes and at least one major cloud platform (AWS, GCP, or Azure).
- Understanding of data modeling, distributed computing concepts, and streaming frameworks (Spark, Flink, or Kafka Streams).
- Strong analytical thinking, communication skills, and a demonstrated sense of ownership, curiosity, and continuous learning.
Desired
- Experience with Twilio Segment, Kafka/Kinesis, or other high-throughput event buses.
- Exposure to infrastructure-as-code (Terraform, Pulumi) and GitHub-based CI/CD pipelines.
- Practical knowledge of generative AI workflows, foundation-model fine-tuning, or vector databases.
- Contributions to open-source data/ML projects or published technical presentations/blogs.
- Domain experience in communications, marketing automation, or customer engagement analytics.
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.
