Remote Machine Learning Engineer - Real-Time ML Systems

Twilio; San Francisco (CA); On-site; USD 183,000 - 229,000; Full time

Benefits offered by this job

Health care insurance

Equity plan

Bonus plan

Paid time off

Job summary

Twilio, a remote-first company, seeks a Machine Learning Engineer to drive innovation in its Data & Observability Substrate group from home. You will develop scalable, low-latency ML-based systems for real-time applications that empower developers and customers.

You will collaborate with engineers, product managers, and security to deliver reliable ML services, own SLAs, and mentor teams in AI-assisted SDLC and best practices.

Qualifications

• 5+ years building, deploying, and operating data/ML systems in production.
• Strong programming with Python, Java, and SQL.
• Experience with ML lifecycle, MLOps, and model evaluation.
• Hands-on with Airflow/Kubeflow and cloud data platforms (SageMaker, Snowflake, DynamoDB, OpenSearch).
• Familiar with Docker, Kubernetes, GitOps/CI/CD (Argo CD) and at least one cloud (AWS/GCP/Azure).
• Ability to ramp up quickly in new domains and communicate well in Agile teams.

Responsibilities

• Design, implement, and maintain scalable, enterprise ML solutions in production.
• Build reproducible ML workflows for data preparation, training, evaluation, and inference.
• Implement monitoring and evaluation to improve data quality, model performance, latency, and cost.
• Collaborate cross-functionally with Product, Data Science/ML, Engineering and Security.
• Demonstrate end-to-end system understanding and articulate design choices.
• Own operational excellence: SLAs, on-call, incident response, and blameless post-mortems.
• Drive AI-assisted SDLC, code reviews, automated testing, and mentoring.

Skills

ML fundamentals

Python

Java

SQL

Strong communication

AGILE collaboration

Tools

Airflow

Kubeflow

SageMaker

Snowflake

DynamoDB

OpenSearch

Docker

Kubernetes

Argo CD

LangChain/LangGraph

Job description

Twilio, a remote-first company, seeks a Machine Learning Engineer to drive innovation in its Data & Observability Substrate group from home. You will develop scalable, low-latency ML-based systems for real-time applications that empower developers and customers.

You will collaborate with engineers, product managers, and security to deliver reliable ML services, own SLAs, and mentor teams in AI-assisted SDLC and best practices.