Founding Machine Learning Engineer (Back-End Focus)

Embark On Talent Ltd; United States; Remote; USD 100,000 - 720,000; Full time

Job summary

An innovative startup is looking for a Founding Machine Learning Engineer to redefine women's health through AI. This remote position offers a unique opportunity to lead the technical build of a groundbreaking product focused on reproductive health. You'll work with longitudinal datasets and machine learning models to create personalized care solutions. As a pivotal member of the team, you will collaborate closely with the founder and expert advisors, making a significant impact in the femtech space. If you're passionate about health tech and eager to build from the ground up, this role is perfect for you.

Qualifications

• Experience as a founding engineer or CTO in early-stage startups.
• Hands-on experience with women's health data is essential.

Responsibilities

• Own the technical development of the second prototype and public-facing demo.
• Retrain and refine an existing DeepSurv-based survival analysis model.

Skills

Python

Machine Learning

DeepSurv

RESTful APIs

TensorFlow

PyTorch

Cloud Infrastructure

Bioinformatics

Education

Bachelor's Degree in Computer Science or related field

Experience in Healthtech

Tools

AWS

GCP

Job description

Founding Machine Learning Engineer (Back-End Focus)

Founding Machine Learning Engineer (Back-End Focus)

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Femtech & Women's Health Talent Specialist | Supporting Founders from Pre-Raise to Scale

Founding Machine Learning Engineer (Back-End Focus)

US - Remote Position

Equity-only to start with potential to move into a salaried position, post-funding

About the Company:

We’re supporting an early-stage femtech startup on a mission to redefine the future of women’s health through data and AI. Their product addresses a longstanding gap in reproductive and hormonal health, using machine learning to support predictive, personalized care.

This isn’t general health data. The company is working with longitudinal hormonal datasets, incomplete time-to-event records, and clinical variables that are often underrepresented in research and poorly understood by non-specialists. That’s why direct experience in women’s health (particularly in the context of aging, menopause, or fertility) isn’t just a nice-to-have, it’s essential.

The first prototype has been developed and validated, and the team is now hiring a founding engineer to lead the next phase; building the second prototype and launching the company’s first live demo.

The Opportunity:

You’ll join at a pivotal moment and take ownership of the technical build. The initial focus is on back-end engineering: improving the existing model, integrating previously excluded data, modernizing the repository, and preparing the system for demo and launch.

While the priority is model and infrastructure work, any experience across front-end deployment is a plus. You’ll work closely with the founder (a machine learning PhD) and have access to expert academic advisors to support your work.

What You’ll Do

• Own the technical development of the second prototype and public-facing demo
• Retrain and refine an existing DeepSurv-based survival analysis model
• Update legacy repository and adapt preprocessing to include new data inputs
• Design and deploy back-end infrastructure and scalable API endpoints
• Manage clinical data integration, including time-to-event and longitudinal variables
• Prepare cloud environments for demo and deployment
• Collaborate with the founder and technical advisors to refine architecture, tooling, and model performance
• (Optional) Support basic front-end integration and web app demo setup

Ideal Candidate Profile

• Experience as a founding engineer, CTO, or first technical hire in an early-stage startup
• Hands-on experience working with women’s health data is essential (including hormonal, reproductive, menopausal, or fertility-related datasets).
• Understands the clinical nuance and complexity of working with underrepresented and longitudinal health data, and the sensitivity required when building tools for this space
• Comfortable in fast-paced, ambiguous environments with minimal structure
• Background in bioinformatics, healthtech, or machine learning for clinical data
• Familiarity with datasets like SWAN or comparable hormonal health studies
• Self-directed, adaptable, and excited by the opportunity to build from scratch

Technical Skillset

• Proficient in Python, with experience in TensorFlow, PyTorch, or equivalent
• Deep understanding of survival analysis (Cox models, DeepSurv)
• Skilled in building and maintaining RESTful APIs and ML inference pipelines
• Experience with cloud infrastructure (AWS, GCP, etc.) and preparing systems for deployment
• Confident working with messy or incomplete datasets and modifying preprocessing pipelines
• Comfortable cleaning and rebuilding outdated repositories
• Bonus: Experience integrating ML back ends into basic front-end applications or live demos

This isn’t a role where tasks are handed out ticket by ticket. Instead, you’ll be expected to scope, prototype, and build full features independently, navigating both strategic decisions and hands-on implementation. If you’ve been a founding engineer before (or have worked in environments where the lines between research, infrastructure, and product delivery blur) you’ll thrive here.

To learn more or confidentially express interest, please contact Natalie Wattenbach at [e-mail]

Seniority level

• Seniority level

  Executive

Employment type

• Employment type

  Other

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development and Health and Human Services

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