# Staff Machine Learning Engineer at Ethos

- Company: Ethos
- What the company does: Get an instant life insurance quote online today! Ethos makes life insurance easy by offering you a dependable quote in seconds. Backed by General Catalyst and Sequoia.
- Company website: https://www.ethoslife.com/
- Type: Startups (AI role)
- Level: Senior
- Location: Remote US
- Work setup: Remote
- Pay: $156K to $275K base salary per year (USD)
- Posted: 2026-11-04
- Apply by: 2026-12-19
- Apply: https://job-boards.greenhouse.io/ethoslife/jobs/8929360002?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/ethos-staff-machine-learning-engineer/

## About the role

We're looking for a Staff Machine Learning Engineer to own the infrastructure that gets our models from development into product and marketing workflows. You'll partner with data scientists and product engineers to build deployment pipelines, feature stores, monitoring systems, and retraining infrastructure across both product and marketing use cases. The right candidate is a data scientist that can also build scalable data architecture: you care about how a model will run at scale, not just how it performs on AUC. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- 7+ years in machine learning engineering, MLOps, or software engineering with a strong ML focus
- Experience deploying and serving real-time production ML models integrated with consumer-facing products (AWS SageMaker or equivalent)
- Strong Python engineering skills: software design, testing, CI/CD, package development, and SQL
- Experience building and maintaining feature pipelines, feature stores, and workflow orchestration (e.g., Airflow)
- Familiarity with Docker, container orchestration, and cloud infrastructure
- Strong communication skills, able to collaborate fluidly with data scientists, product engineers, and non-technical stakeholders

Tags: Software Engineering

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/ethos-staff-machine-learning-engineer/