Job description

Company Overview Function Health is the AI operating system for health, designed to empower people to live 100 healthy years. We are redefining how individuals understand, measure, and improve their health by moving beyond the limitations of traditional care and enabling comprehensive, continuous insight into human biology. Function has been recognized as one of Fast Company’s Most Innovative Companies of 2024 , and is venture-backed by Redpoint and other leading venture firms. Over half a million members have joined Function to take control of their health. Through comprehensive lab testing, MRI and CT imaging, longitudinal data, and guidance from AI and clinical teams, Function gives members a complete and continuous view of their health — and the clarity to act on it. Through acquisitions across imaging, mobile phlebotomy, and supplement tracking and optimization, Function is building an integrated health platform that spans the full path from testing to health clarity to daily action. Function recently announced a $298M Series B and is entering its next chapter of growth. As we scale, the quality and durability of our People systems, data, and insights will directly shape our ability to attract, retain, and support exceptional talent. We are growing our team and seeking out world-class talent that deeply believes in our mission to positively impact global health, has a relentless bias toward action, and a growth mindset. Function fosters a collaborative and dynamic environment where every day we build the future. Role At Function, the person who best understands a piece of data is rarely the person who can safely change it. A data scientist knows exactly how a biomarker should be derived. A clinician knows which reference range is wrong. Today, both have to file a ticket and wait for an engineer. We think that's a platform failure, not a process problem. Our job is to build the paved road that lets the subject matter expert make the change themselves – and lets an agent make it too – without anyone lying awake wondering about the validity or stability of what just shipped. That means the guardrails have to be real: declarative contracts instead of hand-rolled code, CI that diffs the data and not just the diff, validations that gate promotion, lineage that tells you who's downstream, and a rollback that takes one command. Get that right and both your humans and your agents get faster at the same time, for the same reason. That's the work. It's platform engineering, and the users are engineers. Key Responsibilities Three surfaces, all with the same goal – make the safe path the fast path: • Tracking infrastructure. The event pipeline behind product analytics, experimentation, and feature gates. Schemas that are enforced at the source, so a bad event never becomes a bad metric. • Data processing infrastructure. The Bronze → Silver → Gold layer in Databricks. Automated schema evolution, contract tests, backfills that aren't scary, freshness and volume monitors generated from the contract rather than bolted on after. • ML infrastructure. Feature computation and serving, training and eval pipelines, and the plumbing that gets model output back into the product — with the same testing and observability bar as everything else. • Cutting across all three. The self-service story. Templates, local dev and preview environments, policy-as-code for PHI, ownership routing for alerts, and progressive gates so an exploratory model ships freely while a member-facing one earns more scrutiny. Qualifications/Skills • Built internal platform or infrastructure that other engineers actually adopted. You've felt the difference between shipping a tool and getting it used. • Operated production data or ML systems, on call for them, and fixed them under pressure. • Strong Python and SQL. Comfortable in a lakehouse – we use Databricks; Snowflake or BigQuery translates fine. • Designed interfaces and schemas that other teams depend on, then evolved them without breaking those teams. • Thought hard about testing and CI for data or ML, where correctness is statistical and the failure is often silent. • 1-4 years of engineering experience gets you here, but we care about what you've built, not the number. Nice-to-Have Skills and Experiences While the core competencies are essential, the following qualifications will distinguish exceptional candidates: • Declarative pipeline frameworks (dbt, DLT, Dagster, Airflow) • Streaming (Kafka, Spark Structured Streaming) • Data contracts, data diffing, or lineage tooling • Terraform • Feature stores • MLOps and eval tooling • Agentic coding workflows • Healthcare • PHI, or HIPAA experience To be a strong fit, you embody our Core Values • Ruthless Prioritization: • We don’t let perfect get in the way of progress. • We move quickly to drive value, not perfection. • We prioritize what drives impact. • We never compromise on standards of excellence. • Member-First, Always: • We design and deliver like we’re caring for someone we love. • We create calendar, actionable, human experience. • We prioritize responsiveness, peace of mind, and outcomes. • We empower members with truth, clarity, and care. • One Team, Moving Fast: • We are aligned in purpose, prioritization, and speed. • We gather diverse perspectives to make informed decisions. • We clear paths for each other and move fast together. • We communicate clearly and respectfully, rallying around shared goals. • Radical Ownership, Relentless Execution: • We don’t just ship– we own outcomes and drive results. • We act with urgency and precision • We anticipate, initiate, and follow through. • We meet challenges with grit and pragmatism. • We embrace new tech to deliver better outcomes. • Mission Over Ego: • We are ruthlessly aligned to our mission - and leave ego at the door. • We disagree and commit. • We don't tolerate politics or withholding information. • We operate with honesty, transparency, and respect. • Sustained Integrity in Every Detail: • We earn trust by obsessing over accuracy, quality, and clarity in everything we do. • We prioritize clinical precision - data must be right. • We sweat the details because outcomes depend on them. Why You'll Love Working With Us We value our team at Function and offer a competitive salary and benefits package, flexible working hours, and a dynamic work environment where creativity and innovation are encouraged. If you are a highly motivated and experienced individual who is passionate about using technology to improve people’s lives, we would love to hear from you. At Function, we celebrate diversity and are committed to building a diverse and inclusive workforce. As an equal opportunity employer, we do not discriminate on the basis of race, color, gender identity, ancestry, religion, age, sexual orientation, national origin, disability, marital status, Veteran status, or any other occupationally irrelevant criteria. Join the Function Health team and become a part of our mission to build a healthier future for all. Discover more about us and how we're changing the face of healthcare at Function Health . Important Notice: Legitimate communication from the Function Health team will always come from an email address ending in @functionhealth.com. Function Health will never request personal information such as banking details or payment during the hiring process. Please be cautious of communications or job offers that come from other email domains, instant messaging platforms, or unsolicited calls. If you ever have doubts about the legitimacy of a communication, please reach out to us directly at talent@functionhealth.com.

Requirements

Must-haves

Company Overview
That's the work. It's platform engineering, and the users are engineers.
Three surfaces, all with the same goal – make the safe path the fast path:
Tracking infrastructure. The event pipeline behind product analytics, experimentation, and feature gates. Schemas that are enforced at the source, so a bad event never becomes a bad metric.
ML infrastructure. Feature computation and serving, training and eval pipelines, and the plumbing that gets model output back into the product — with the same testing and observability bar as everything else.
Qualifications/Skills
Built internal platform or infrastructure that other engineers actually adopted. You've felt the difference between shipping a tool and getting it used.
Operated production data or ML systems, on call for them, and fixed them under pressure.
Strong Python and SQL. Comfortable in a lakehouse – we use Databricks; Snowflake or BigQuery translates fine.
Designed interfaces and schemas that other teams depend on, then evolved them without breaking those teams.
Thought hard about testing and CI for data or ML, where correctness is statistical and the failure is often silent.
1-4 years of engineering experience gets you here, but we care about what you've built, not the number.
While the core competencies are essential, the following qualifications will distinguish exceptional candidates:
Declarative pipeline frameworks (dbt, DLT, Dagster, Airflow)
Streaming (Kafka, Spark Structured Streaming)
Data contracts, data diffing, or lineage tooling
Feature stores
MLOps and eval tooling
Agentic coding workflows
PHI, or HIPAA experience
To be a strong fit, you embody our Core Values
Ruthless Prioritization: • We don’t let perfect get in the way of progress.
We move quickly to drive value, not perfection.

Nice-to-haves

Nice-to-Have Skills and Experiences

Application prep

Use the role’s language and application details while tailoring your materials.

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aimlpythonsql

Platform: gem
Effort: medium