Resumen del rol

Machine Learning Engineer

Requisitos y responsabilidades

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Details

  • 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.
  • 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.
  • 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.
  • Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $138,700 - $173,400.
  • Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $146,800 - $183,600.
  • Based in the San Francisco Bay area, California: $163,100 - 203,900.
  • This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.
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