Senior AI/ML Engineer

Metriport • San Francisco, CA

39d • $200,000 - $260,000 • Hybrid

About The Position

This is the first Machine Learning Engineer role at Metriport. We have access to the richest clinical datasets in the country — longitudinal medical records for hundreds of millions of individuals — and we've barely scratched the surface of what can be learned from it. You'll own machine learning at Metriport end-to-end: from framing the problem with customers, to training the models, to serving them in production and keeping them honest. This is applied ML on messy, high-dimensional, real-world healthcare data - not a research role, and not an LLM-wrapper role. You have deep ML fundamentals, from classical methods through deep learning. You can take a prediction problem from a linear baseline to gradient-boosted trees to a neural network - and you know when each one is the right answer. You've shipped models to production and lived with them: you have opinions about evaluation, monitoring, retraining, and what can break after launch. You're deeply experienced with ML, but still have strong eng chops: you can stand up a service, write the IaC, instrument it, and own it end-to-end. Python is home; TypeScript, AWS, and SQL aren't going to scare you. You're pragmatic about LLMs. You've used them where they win and you know where a smaller, cheaper, more reliable model wins instead. You're comfortable with messy, real-world data: sparse, inconsistent, high-dimensional, and full of surprises. Healthcare data is all of these at once. You're entrepreneurial-minded with an olympian-level work ethic (about half our engineering team are former founders). When someone scopes a project for 3 weeks, you ask "why can't it be done in 3 days?" - and you help others develop that same instinct. You're a hacker at heart, with a good sense of which rules should, and shouldn't, be broken.

Requirements

• 7+ years building ML systems that run against real data at scale.
• Strong grounding across the ML spectrum: regression and tree-based methods, feature engineering and dimensionality reduction, and deep learning. You've built and trained models yourself, not just orchestrated APIs.
• A track record of ML delivering measurable results in production.
• Strong software engineering fundamentals: you've built or operated large-scale backend systems on the cloud (ideally AWS) and can own training pipelines, model serving, and monitoring end-to-end.
• Strong data skills: SQL, working with large datasets, and building the pipelines that feed your models.
• You're located in San Francisco or the Bay Area (or willing to relocate).

Nice To Haves

• Healthcare standards/technologies: FHIR, HIE, IHE, EHR/EMR, NPI, TEFCA, ADT, HL7, HEDIS, RAF, SNOMED, LOINC, ICD-10, etc.
• Founder experience, or being the first/only ML hire at an early-stage startup.

Responsibilities

• Build the models, and the ML platform underneath them, that turn raw clinical data into intelligence our customers act on.
• Building predictive models on clinical data at scale: risk stratification, expected utilization / prediction, care-gap detection.
• Owning the full ML lifecycle: problem framing, feature engineering over sparse and high-dimensional clinical data, training, evaluation, deployment, and monitoring for drift and degradation in production.
• Turning unstructured clinical data into structured, usable records: parsing PDFs, images, doctor notes, etc.
• Standing up our ML infrastructure: training and inference pipelines, experiment tracking, model versioning, and evals - so that every model we ship is measurable, debuggable, reliable.
• Working directly with founders, engineers, and customers to figure out which ML problems are highest-leverage to solve next.
• Building a model that predicts expected hospitalizations for new patients from their medical history.
• Turn freeform doctors' notes and scanned documents into structured data we can add to patients' medical records.
• Build classifiers to categorize billions of clinical documents with incomplete metadata.

Benefits

• Competitive equity + compensation package
• Full family Platinum health insurance, dental, and vision coverage
• 401(k) retirement plan + matching
• Flexible work from home or in-office
• Healthy lunches are complimentary when working in-office (and breakfast + dinners as needed)
• Quarterly company off-sites with the team
• MacBook provided by us
• Unlimited PTO (we work hard, but trust you to take time you need to be at your best)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed