Staff Machine Learning Engineer (Fully 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

• As a Staff Machine Learning Engineer, you will own the infrastructure that gets models from development into product and marketing workflows.
• You will partner with data scientists and product engineers to build deployment pipelines, feature stores, monitoring systems, and retraining infrastructure.

What You’ll Do:

• 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.

Who You Are:

• You have 7+ years in machine learning engineering, MLOps, or software engineering with a strong ML focus.
• You have experience deploying real-time ML models on AWS SageMaker and strong Python engineering skills.
• You are biased toward ownership, bridge data science and engineering, and raise the team’s bar through code review and mentorship.

What We Offer:

• A competitive base salary range of $156,000 - $275,000 per year, plus bonus, equity, and benefits.
• The opportunity to work remotely within the US with a collaborative, inclusive culture.
• The chance to shape the ML infrastructure at a leading insurtech company.

Ethos

Ethos is a leading life insurance technology company on a mission to democratize access to life insurance and empower agents at scale. With a three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers, and is publicly traded on Nasdaq.