# Machine Learning Engineer
**Company:** [Twilio](https://hotfix.jobs/companies/twilio)
**Location:** Remote
**Salary:** $139K-$204K
**Experience:** 3+ years
**Skills:** Python, SQL, Airflow, Dagster, Snowflake, BigQuery, Redshift, MLflow, SageMaker, Vertex Ai, Docker, Kubernetes, AWS, GCP, Azure
**Posted:** 2026-06-25
> Design, build, and operate cloud-native data and ML infrastructure powering real-time intelligence for Twilio products. Requires 3-5 years of production ML/data systems experience and strong Python/SQL skills.
## Job Description
## 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.

## Requirements
- 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.

## Nice-to-Haves
- 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.

## Compensation & Benefits
- Health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.
- This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan.
**Apply:** https://hotfix.jobs/jobs/machine-learning-engineer-at-twilio-f66880d4-a8a1-48fe-a3d2-23b905c2e664
**Canonical:** https://hotfix.jobs/jobs/machine-learning-engineer-at-twilio-f66880d4-a8a1-48fe-a3d2-23b905c2e664