Machine learning engineer h1.location_city

About Keebler Health

Keebler Health is building the operating system for value-based care. Our mission is to help risk-bearing healthcare organizations thrive in value-based arrangements by unlocking the full power of their data. We empower leading primary care groups, ACOs, and health plans to act on real-time insights that improve outcomes, reduce costs, and fuel sustainable growth.

We're a fast-moving, high-performing team, and we’re looking for people who share our bias toward speed, urgency, and excellence. As a member of the team, you won’t just write code or stay in your lane—you’ll shape critical systems, innovate quickly, and set a high bar for a product that supports the future of U.S. healthcare.

Role Overview

As a Delivery Engineer, you will sit at the intersection of client success, data operations, and engineering. You’ll manage the flow of data from client intake through to clean, validated deliverables — ensuring each engagement (from a 50-patient pilot to a full population review) runs smoothly, transparently, and with measurable impact.

You’ll be both a project manager and a technical operator: coordinating across internal teams, running scripts and pipelines, and ensuring our outputs meet Keebler’s high standards for accuracy, security, and clinical integrity.

Responsibilities

• Serve as the primary workflow owner for assigned clients, including pilots and live accounts.
• Effectively communicate data requirements, timelines, and expected outcomes with the team and clients.
• Ingest, clean, and process client-submitted data (e.g., spreadsheets, claims, encounter notes, lab results).
• Pull, transform, and validate datasets using Python, SQL, and related tools.
• Develop scripts and lightweight tools to automate recurring data preparation and delivery workflows.
• Partner with Engineering to troubleshoot ingestion pipelines, QA outputs, and improve automation.
• Ensure all deliverables meet internal standards for accuracy, compliance, and HIPAA security.
• Package and deliver client results, working with clinical SMEs to add interpretive context.
• Track and report client health metrics to support renewals and continuous improvement.
• Help refine and improve internal delivery playbooks, templates, and documentation as the team scales.

Qualifications

• Proficiency in Python for data manipulation and automation (pandas, requests, etc.).
• Experience working with healthcare data (claims, clinical notes, lab results, or EHR exports).
• Familiarity with Excel/CSVs, and basic SQL for data extraction and validation.
• Strong communication and project management skills; able to translate between technical and clinical contexts.
• Must be a self-starter who is comfortable working in a fast-paced, startup environment with evolving specs and limited documentation.

Bonus Points For

• Experience in health tech startups or consulting.
• Familiarity with EHR systems and value-based care models.
• Exposure to risk adjustment, RAF scoring, or clinical data quality workflows.

What Success Looks Like

• Efficiently executing and delivering results for multiple independent workflows at once.
• Internal teams utilize your scripts and tools to scale operations efficiently.
• Pilots demonstrate the speed and comprehensiveness of Keebler’s review process — creating clear “wow” moments.
• Data integrity and compliance are consistently flawless.
• Client satisfaction and renewal rates remain high.

Whether you apply through the website, or email careers@keebler.health please include:

• A highly personalized, bold, and hilarious “Keebler Health–style” introduction that grabs attention - outgoing, fun, and uniquely you (not uniquely ChatGPT). Think: confident, high-energy, slightly irreverent (but still professional), with a smart nod to healthcare, value-based care, and the fact that we’re building something real.
• Your resume
• A link to your profile

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