Machine Learning Engineer

Twilio

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$174,960–$213,840 / yr
Posted
3 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $223k
This role $194k
$164k most similar roles pay here $276k

This role pays less than 73% of similar roles. Most pay $192,050–$254,750 — the shaded band above. At the midpoint, this role pays about $194k versus about $223k for comparable roles.

Based on 240 similar postings.

Employer

About Twilio

Twilio is a cloud communications platform that provides APIs and software, allowing developers to embed voice, messaging, video, and email functionalities directly into their applications.

Twilio currently has 36 open roles on FindRole.

Listed pay typically runs $155,520–$194,400 across 33 roles with salary data.

Most-posted roles

View all roles at Twilio

At a glance

TL;DR · Machine Learning Engineer

As a Machine Learning Engineer (L3) within the Data & Observability Substrate organization, you will join a builder-focused team to develop and maintain scalable, low-latency, ML-based systems for real-time applications. You will bridge product and engineering to translate business ideas into technical solutions for streaming anomaly detection, recommendation systems, predictive modeling, and agentic AI frameworks. Your daily work involves designing reproducible workflows for data preparation, training, and inference while implementing monitoring frameworks to optimize model performance and cost. You will utilize Python, Java, and SQL alongside tools like Airflow, Kubeflow, SageMaker, Snowflake, and DynamoDB. The role requires expertise in MLOps, containerization via Docker and Kubernetes, and distributed streaming frameworks like Spark or Kafka. You will solve complex problems involving LLMs, RAG, and vector databases to deliver personalized customer experiences within the communications platform space.

What does a Machine Learning Engineer earn in Remote?

Median $229700 from 72 postings across 27 companies.

See salary data

What you'll do

  • Translate business requirements into measurable machine learning problem statements and technical specifications.
  • Design, implement, and maintain scalable, enterprise-grade ML solutions in production environments.
  • Build reproducible ML workflows for data preparation, training, evaluation, and inference using MLOps tools.
  • Implement monitoring and evaluation frameworks to optimize model performance, latency, and cost.
  • Manage operational excellence including SLAs, on-call rotations, incident response, and post-mortems.
  • Drive engineering excellence through automated testing, code reviews, and AI-assisted development practices.

What we're looking for

  • Strong foundation in ML/AI including statistics, probability, and optimization applied to real-world problems.
  • 5+ years of experience building, deploying, and operating data and ML systems in production.
  • Proficiency in Python, Java, and SQL with strong software engineering fundamentals like system design and version control.
  • Hands-on experience with workflow orchestration (e.g., Airflow, Kubeflow) and cloud data platforms/storage.
  • Experience with the ML lifecycle, MLOps tooling, LLM/agent frameworks, and model evaluation tools.
  • Working knowledge of containerization (Docker, Kubernetes), GitOps/CI/CD tools, and at least one major cloud platform.
  • Understanding of data modeling, distributed computing, and streaming frameworks; familiarity with GPU-based implementation is a plus.
  • Advanced degree in a relevant field (preferred).

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