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.
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
More about this role
Ethos (Nasdaq: $LIFE) is a leading life insurance technology company on a mission to protect families by democratizing access to life insurance and empowering agents at scale. With its robust three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers alike. Ethos offers instant, accessible products and a seamless online process that requires no medical exams and just a few health questions; it eliminates traditional barriers, making it easier than ever for everyone to protect their families. Ethos is redefining how life insurance is bought, sold, and underwritten.
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.
- Own the deployment and production lifecycle...
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