Machine Learning & Data Engineer - L3

Summary

Join Twilio’s AI & Data Platform team as an L3 Machine Learning and Data Engineer. You will design, build, and operate the cloud-native data and ML infrastructure that powers every customer interaction, enabling Twilio’s product teams and customers to move from raw events to real-time intelligence. This hands-on role offers clear technical ownership, mentoring, and growth. You will architect, implement, and maintain scalable data pipelines and feature stores. Responsibilities include building reproducible ML workflows, integrating event streams from Twilio products, monitoring data quality and model performance, and partnering with other teams. You'll also automate deployment and produce clear documentation. The role requires a B.S. in a related field or equivalent experience, 1–3 years of experience building and operating data or ML systems, proficiency in Python and SQL, and experience with various tools and technologies. The position is remote but not eligible for hiring in certain states.

Requirements

• B.S. in Computer Science, Data Engineering, Electrical Engineering, Mathematics, or related field—or equivalent practical experience
• 1–3 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

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• Competitive pay
• Generous time off
• Ample parental and wellness leave
• Healthcare
• A retirement savings program
• Health care insurance
• 401(k) retirement account
• Paid sick time
• Paid personal time off
• Paid parental leave