Machine Learning Engineer

Machine Learning Engineer at HealthLeap AI

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HealthLeap builds AI that helps clinicians prioritize patients, surfaces the right data, and gets patients the care they need earlier, so they can leave the hospital sooner. We integrate with hospital electronic health record systems, screen 100% of patients daily, and risk‑rank them in real time. Clinicians at Cedars‑Sinai, Penn Medicine, Houston Methodist, Emory, and Intermountain Health begin each day with HealthLeap. Real results : 39% more diagnoses, 4 days earlier detection, $11M / year ROI at Cedars‑Sinai, 7× revenue growth in 7 months.

We started with malnutrition and are expanding to every major condition. With backing from Sequoia, First Round, we build a platform that screens every patient for everything and drives tangible outcomes.

Role Overview

We're seeking an exceptional Machine Learning Engineer to join our engineering team and accelerate our product expansion. This role is both self‑directed and entrepreneurial—handling immediate production needs while independently driving new AI modules for emerging conditions. You'll work closely with our CEO and small team to productionize models, enhance our platform, and leverage our vast healthcare data to create foundation models that transform patient care.

Key Responsibilities

Productionize and optimize ML models for deployment, focusing on speed, monitoring, and reliability in a high‑stakes healthcare environment.

Build and improve data processing pipelines for large‑scale tabular and text data from EHRs, including retraining workflows and integrations.

Experiment with frontier AI technologies, such as LLMs and agentic systems (e.g., using tools like LangChain), to enhance clinical note analysis and predictive capabilities.

Independently spin up proofs‑of‑concept (POCs) for new conditions (e.g., pressure ulcers, CHF readmissions), absorbing business / clinical context from customer calls and iterating to production.

Collaborate on MLOps tasks, including model improvements, email integrations, and ensuring smooth handling of massive datasets.

Contribute to our mission by helping scale the platform across hospitals, conditions, and potentially outpatient / international settings.

Requirements

Strong software engineering skills with proven ML experience : Productionizing models (tabular / text data preferred; not pure vision specialists) and building scalable pipelines.

Hands‑on experience with LLMs in production; familiarity with classic ML techniques.

3‑5+ years of relevant experience from a high‑growth environment.

Bachelor's or Master's in Computer Science, ML, or related field.

Comfortable in chaotic, high‑agency startup settings—excited by rolling up sleeves and navigating regulations / compliance thoughtfully.

Passionate about AI’s potential in healthcare; business‑oriented with a focus on impact, not just research.

Excellent problem‑solving, fast experimentation cycles, and ability to work independently while collaborating in a small team.

Nice‑to‑Haves

Experience building agentic workflows or from frontier labs (applied side).

Background in applied AI companies with strong product traction (not hype‑driven firms).

Interest in healthcare data (e.g., from research labs with practical applications), though not required.

Side projects demonstrate productionization (e.g., turning prototypes like landing agents into reliable systems).

Resourceful, fast learner with a network that could attract top talent.

Benefits

Competitive salary with performance‑based incentives.

Comprehensive Healthcare Benefits – we cover 100% of premiums for employees.

Unlimited Paid Time Off – our recommended 20 PTO days per year lets you schedule your work around your life.

401(k) match of up to 4% of employee salary.

Laptop and equipment budget to set up your at‑home office environment.

Lunch, snacks, and drinks are provided in the office to ensure you never go hungry.

Opportunity for professional growth in a dynamic, fast‑paced startup environment.

Location

San Francisco (hybrid). Compensation is dependent on experience, overall fit to our role, and candidate location.

Apply

If you’re passionate about applying frontier AI to real-world impact, join us in building healthcare’s future.

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