Senior ML Infrastructure Engineer

Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.

Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.

AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.

We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.

As a Senior ML Infrastructure Engineer, you will own the data infrastructure that powers our underwriting, claims, and operational workflows, translating complex business logic into reliable, scalable pipelines that the entire company depends on.

• Own our data infrastructure and the core data platform pipelines that drive underwriting and claims.

• Partner with data scientists and actuaries to turn business logic into production code, owning the underwriting pipeline end-to-end.

• Set the standards for how we build, monitor, and operate data systems — establishing SLAs, on-call practices, and monitoring that the team relies on.

To give you a sense of the impact you'll have, here are some initial projects you could own:

1. →

   Underwriting Pipeline & API: Own and improve the pipelines and API that sit at the core of Arlo's underwriting engine. You'll work directly with data scientists and actuaries to translate underwriting logic into production code and ensure the systems that run it are fast, observable, and reliable.

2. →

   Claims Ingestion & Enrichment Logic: Build and maintain the ingestion pipelines that bring third-party claims data into our platform. You'll design systems that handle messy, real-world claims data at scale and make it usable for downstream analytics, underwriting, and operations.

3. →

   Company-Wide Data Foundations: Architect and build the data infrastructure that powers operational workflows across the business - quoting portal, cost containment, member engagement - and extend it to non-underwriting teams, including sales ops, finance, and clinical.

This role is a great fit if you are an engineer who takes pride in writing high-quality, maintainable code and is energized by owning data systems end-to-end.

• A strong track record of building scalable data systems and pipelines in production, with deep proficiency in Spark, Databricks, and modern data processing infrastructure (AWS or equivalent).

• Fluency across our stack: SQL, PySpark, Python, and Git. You write maintainable code and hold a high bar for code quality on your team.

• The ability to own workstreams end-to-end with minimal oversight. You make sound judgment calls independently, flag the right risks, and make the people around you better through standards, reviews, and process improvements.

• Strong communication skills and a highly analytical mindset. You can work with non-technical partners — actuaries, ops, clinical — to turn requirements into action, and you test and analyze your own work before it ships.

• Prior experience in a regulated space like healthcare or insurance.

• Experience supporting data science or actuarial teams in production environments.