Twilio
Machine Learning Engineer
Rol remoto de Engineering con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles1 país aceptado
Señal de seniorityNivel abierto
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Machine Learning Engineer
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
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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