Staff Machine Learning Engineer, Ethos Life
$156-275k
Life insurance provider
Be an early applicant
Life insurance provider
501-1000 employees
Be an early applicant
$156-275k
501-1000 employees
Company mission
To protect the next million families.
Role
Who you are
- 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
- Bias toward ownership; you see a gap in the infrastructure and close it
- Working knowledge of ML methods: supervised learning, Bayesian models, causal inference, enough to debug a model without a data scientist in the room
- Marketing measurement: attribution, media mix modeling, or ad platform integrations
- Dbt or data warehouse tooling
- Experience in insurtech, fintech, or other regulated industries
- Gets in the weeds without losing the bigger picture
- Knows the tradeoffs between over-engineered infrastructure and pragmatic solutions, and picks the right one
- Bridges data science and engineering, fluent in both worlds and trusted by both teams
- Raises the team's ML engineering bar through code review, documentation, and mentorship
What the job involves
- 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 of models powering product experiences: coverage recommenders, user-to-channel routing, and agent assignment logic
- Build and maintain feature pipelines that feed real-time inference for consumer-facing product surfaces
- Implement automated monitoring and alerting for data drift, feature quality issues, and model degradation
- Develop CI/CD pipelines and retraining infrastructure that let data scientists ship iterative improvements without engineering bottlenecks
- Deploy and operationalize marketing models: attribution, incrementality, and media mix and automate feedback loops to ad platforms
- Build reliable data pipelines that deliver clean, timely inputs to marketing models and measurement workflows
- Own model health monitoring and dependency management across the marketing model inventory
Our take
Ethos was founded to increase the transparency of life insurance, making it accessible and affordable to all. The company wants to add openness to the process; losing a loved one is hard enough before one even considers financial implications, particularly with the loss of a primary earner.
Ethos uses predictive technology to rapidly quote life insurance rates and verify an applicant’s medical information. This expedited process allows most users to secure life cover on the same day they apply, a process which normally takes a number of weeks. The company works with some of the biggest providers in the industry, including Legal & General America, AAA Life and Ameritas Life Insurance Corp.
Ethos has been one of the more heavily publicized of the recent wave of insurtech companies, with investors such as Google as well as celebrities Will Smith and Jay Z, taking its valuation to over $2B and putting it in a great spot for future growth.
Steph
Company Specialist at Welcome to the Jungle
Insights
72% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Jul 2021
$100m
SERIES D
May 2021
$200m
SERIES D
Total funding: $406.5m
Company benefits
- Comprehensive benefits packages: Awesome medical dental, vision and as applicable insurance coverage and retirement plans (in the US we offer a 401(k) plan).
- Company Equity: We want you to feel and act like an owner.
- Rest, relax & recharge: We encourage our employees to take time off, in addition to our fully paid global company holiday schedule. When you need time away from work, we have paid and flex time options based on your role and location, and additional paid leave programs.
- Generous leave programs: As well as offering a wide array of leave programs, new parents can take leave with 100% wage replacement. Our healthcare plans offer coverage on family planning and fertility.
Company HQ
Berkley Square - Headway, Austin, TX
Leadership
Peter Colis
(Co-Founder & CEO)After an MBA at Stanford, Peter co-founded Ovid Corp in 2014, where he worked as CEO for 4 years before co-founding Ethos in 2016. He has worked as CEO since, alongside serving as a Sequoia Capital Scout.
Lingke Wang
(Co-Founder)After working as an Investment Banker at Morgan Stanley Lingke gained an MBA from Stanford. He then co-founded Ovid Corp. an insurance company before Ethos.
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