Staff ML Engineer – Production & MLOps Lead (Remote)

Ethos; United States; Remote; USD 156,000 - 275,000; Full time

Benefits offered by this job

Remote within US

Bonus & equity

Benefits

Job summary

Ethos is seeking a Staff Machine Learning Engineer to own the end-to-end deployment of ML models used in product and marketing workflows. You will partner with data scientists and engineers to build production pipelines, feature stores, and monitoring systems in a scalable, reliable way.

You will deploy real-time models on AWS SageMaker, design robust data pipelines for attribution and media mix, and establish automated monitoring for data drift and model degradation.

Qualifications

• 7+ years in machine learning engineering, MLOps, or software engineering with a strong ML focus.
• Experience deploying real-time ML models on AWS SageMaker.
• Bias toward ownership, bridging data science and engineering, and mentoring through code reviews.

Responsibilities

• Own the deployment and production lifecycle of models powering product experiences like coverage recommenders and user-to-channel routing.
• Build reliable data pipelines for marketing models, including attribution and media mix, and automate feedback loops to ad platforms.
• Implement automated monitoring and alerting for data drift, feature quality issues, and model degradation.

Skills

Machine learning engineering

MLOps

Ownership

Mentorship

Python

Tools

AWS SageMaker

Job description

Ethos is seeking a Staff Machine Learning Engineer to own the end-to-end deployment of ML models used in product and marketing workflows. You will partner with data scientists and engineers to build production pipelines, feature stores, and monitoring systems in a scalable, reliable way.

You will deploy real-time models on AWS SageMaker, design robust data pipelines for attribution and media mix, and establish automated monitoring for data drift and model degradation.