ML Engineer
Added
3/12/2026
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This Role is Closed
This is a Featured Job
Note: We've kept the name of the company private. If you'd like to know the company before requesting an intro, just email us at hello [at] fractionaljobs.io
About Us
We're building a platform that gives families 24/7 access to board-certified pediatricians from home, using an app paired with an at-home diagnostic kit.
We've raised a Series A from top investors, and we're handling thousands of visits a week across the country.
About the Work
Our ML capabilities are still early, and we want expertise to guide our R&D direction and general best practices. We're looking for a Fractional ML Engineer to serve as a technical compass for our engineering team, advising on experiments, model architecture, and data engineering decisions.
Specifically, you'll:
- Help us improve the performance of our existing models
- Example: Our CNN that classifies the medical actionability of otoscope images
- Advise our engineering team on which new experiments to run and how to interpret results
- Example: Predict diagnoses based on structured survey responses and vitals for better routing to providers
- Use experiment results to guide improvements to our data inputs (surveys, patient vitals, medical history, and more)
- Build a benchmark harness to compare our model performance against external vendors
- Identify gaps in our training data that could introduce bias or make models harder to audit, and recommend how to fix them
- Guide us on MLOps best practices for deploying, monitoring, and retraining models
- Work most closely with our Head of Engineering, Data Scientist, and Senior Engineer
Tech Stack:
- Python / Django
- GCP
- Postgres
- Vertex AI and Gemini
- PyTorch
- Sklearn
About You
You MUST have:
- Significant, hands-on ML expertise across both structured and unstructured data:
- Very comfortable with classical ML techniques for structured/tabular data - random forests, XGBoost, linear regression, and similar
- Experience with deep learning for unstructured data - particularly image classification (CNNs) and NLP
- Led ML efforts for engineering orgs where you're setting direction and strategy
- Data engineering experience - cleaning, structuring, and preparing data to improve model performance
- Based in the USA only
Some nice-to-haves:
- Worked on healthcare-related ML problems, particularly around patient data, triage, or diagnosis
- Experience identifying and mitigating bias in training data (e.g gender, race)
- MLOps expertise
How to Get in Touch
Hit that "Request Intro" button below. Include any relevant links so we can get to know you better.
Your brief intro note should clearly address:
- The companies you've led ML efforts for, and how you guided the eng team on where to focus
- Your structured/tabular ML expertise, and an example recent problem solved
- Your unstructured ML expertise, and an example recent problem solved
- Any MLOps expertise
If we think there's a fit, we'll reach out to schedule an intro call. Looking forward!
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