Arlo

• Developing mission-critical software at Palantir
• Scaling a Y Combinator startup from the very first hire to Series A (50+ employees)
• Creating actuarial models used by major health insurers
• Led sales at major, nationwide insurance brokerages
• Leading patient operations teams at a high-growth health plan startup

About the Role

Key Responsibilities:

• Design and build scalable data pipelines that process billions of healthcare claims records
• Develop robust ETL workflows to ingest, normalize, and transform medical data from multiple sources
• Create infrastructure for real-time ML inference serving hundreds of millions of predictions
• Build developer tooling to accelerate the work of our data scientists and ML engineers
• Architect and implement monitoring systems to ensure data quality and model performance
• Optimize PySpark code for feature construction to improve performance and efficiency

Projects You'll Lead:

Healthcare Data Platform:

• Build a unified data platform that ingests medical data from diverse sources and normalizes it for both training and inference
• Develop workflow orchestration tools to automate complex data processing pipelines
• Create CI/CD pipelines for reliable deployment of data transformations and ML models
• Refactor and optimize existing PySpark code to enhance performance and scalability

ML Production Infrastructure:

• Design and implement real-time inference systems that can handle high-volume prediction requests
• Build infrastructure for A/B testing and controlled model rollouts
• Develop monitoring tools to track model performance and data drift in production

What We Value

• Autonomy and Curiosity: You’re eager to learn, can work independently, and thrive when given the freedom to solve problems your way.
• Judgment and Adaptability: You’re skilled at prioritizing projects and making sound decisions in a dynamic, fast-paced environment.
• Collaboration: You communicate effectively with both technical and non-technical teammates, always keeping the end-user in mind.
• Ownership: You’re ready to own projects end-to-end, from designing architecture to writing clean, maintainable code.

Requirements

• 3+ years of experience as a backend engineer, data engineer, or software engineer with exposure to data pipelines and large-scale infrastructure.
• Strong understanding of data structures, algorithms, and scalable system design.
• Demonstrated ability to design secure, robust, and scalable infrastructure for data and backend systems.
• Hands-on experience with big data tools (e.g., Spark) and pipeline orchestration platforms (e.g., Dagster, Airflow, Prefect).
• Proficiency in a backend programming language like Python and solid SQL skills for querying and database design.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and their data services.

Why Join Us?

• Be part of a team building industry-changing technology that directly impacts our clients and millions of people.
• Work alongside a talented team that thrives on innovation, transparency, and collaboration.
• Join a team that pushes each other to excel, supports one another through challenges, and builds each other up to achieve our best work together.
• Enjoy competitive medical, dental, and vision coverage, plus a generous vacation policy—work hard, recharge when needed, and come back ready to make an impact.

Process

1. 30-minute introductory call with Karthik (CTO/COO & Co-Founder)
2. Take-home coding challenge
3. 60-minute review of your coding challenge with Karthik (virtual)
4. Onsite interview at our NYC office (or virtual for remote), including technical and behavioral/cultural components