Machine Learning Engineer

Twilio

Machine Learning Engineer designing and building cloud-native data and ML infrastructure for Twilio's AI & Data Platform team. Collaborate with product and data science teams on customer interactions.

Posted 6/25/2026full-timeRemote • California, Connecticut, New Jersey, New York, Pennsylvania, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $138,700 - $183,600 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureBigQueryCloudDockerETLGoogle Cloud PlatformKafkaKubernetesPythonSparkSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

B.S. in Computer Science, Data Engineering, Electrical Engineering, Mathematics, or related field—or equivalent practical experience.
3–5 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.

Benefits

Comp & perks

Competitive pay
Generous time off
Ample parental and wellness leave
Healthcare
Retirement savings program
Participation in Twilio’s equity plan and corporate bonus plan

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonSQLETLELTAirflowDagsterSnowflakeBigQueryRedshiftMLflow

Soft Skills

analytical thinkingcommunication skillsownershipcuriositycontinuous learning