Machine Learning Engineer

HealthLeap is an AI start-up revolutionizing healthcare through predictive analytics, initially focused on disease-related malnutrition—a critical form of patient deterioration affecting virtually every hospital condition. Our mission is to maximize health outcomes globally by building a scalable AI platform that screens patients comprehensively using electronic health records (EHRs), labs, clinical notes, and more.

We're experiencing explosive growth, with contracts and pilots at top US health systems like Cedars-Sinai, Intermountain Health, Penn Medicine, and many others. We have unprecedented access to EHR data (far more than competitors : 10s of billions of tokens per hospital + vast structured data across 100% of inpatients), positioning us to expand into additional conditions like pressure ulcers, congestive heart failure, infections, readmissions, and mortality predictions. With a unique strategy and no direct competitors (due to our 2+ year lead and regulatory advantages), we are setting out to become a $100B+ company.

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—where you\'ll handle 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 demonstrating productionization (e.g., turning prototypes like landing agents into reliable systems).

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

We Provide :

Competitive salary with performance-based incentives

Comprehensive Healthcare Benefits - we cover 100% of premiums for employees

Unlimited Paid Time Off - we need you at your best at all times. Our recommended time off of 20 PTO days per year lets you schedule your work around your life.

401K 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.

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

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