- Location
- United States
- Workplace
- Remote
- Employment
- Full time
- Level
- Senior
- Posted
- 28 April
About this role
Paradigm Health is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. Our platform enhances trial efficiency and reduces the barriers to participation for healthcare providers. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm’s seamless infrastructure implemented at healthcare provider organizations, will bring potentially life-saving therapies to patients faster.
Our team hails from a broad range of disciplines and is committed to the company’s mission to create equitable access to clinical trials for any patient, anywhere. Join us, and bring your expertise, passion, creativity, and drive as we work together to realize this mission.
Please Note: We are posting this position in anticipation of a hiring need later this year; as such we are NOT in an active recruiting cycle for it, but starting the process of advertising the role to attract talent and applications for those who are interested in future opportunities like this at Paradigm Health.
Role Summary:
As a Senior Machine Learning Engineer, you will take a leading role in designing and deploying sophisticated ML models, including GenAI and LLM-based solutions, that optimize clinical trial workflows and patient engagement. This position offers an opportunity to impact healthcare by developing state-of-the-art models that enhance trial design, accelerate patient recruitment, and improve overall trial efficiency. You will contribute to both high-level architecture decisions and hands-on implementation, driving the technology forward and influencing ML strategies across Paradigm.
Responsibilities:
Model Development & Deployment: Lead the development, testing, and deployment of ML models and pipelines, with a focus on scalability and integration into production systems.
Advanced GenAI/LLM Applications: Design and refine GenAI/LLM-based models to streamline and automate clinical trial operations, from data gathering to real-time performance monitoring.
Cross-Functional Collaboration: Partner with clinicians, informaticists, data scientists, and engineers to build solutions aligned with Paradigm’s mission and goals.
Infrastructure & Performance Optimization: Drive improvements in model deployment infrastructure, develop monitoring tools, and refine model performance to ensure robust production-level reliability.
Technical Leadership & Mentorship: Mentor junior ML engineers, contributing to team knowledge-sharing and establishing best practices for data science and machine learning.
Strategic Communication: Present complex technical insights and results to both technical and non-technical stakeholders, advocating for data science-driven strategies that align with business objectives.
Qualifications:
Education: Master’s or PhD in computer science, statistics, machine learning, or a related field.
Experience: 5+ years of experience as a machine learning engineer, with a proven track record in healthcare, life sciences, or a related field.
Technical Skills: Deep expertise in training, fine-tuning, and deploying ML models, including experience with GenAI/LLMs. Proficiency in Python, SQL, and familiarity with cloud infrastructure and ML engineering best practices.
Production-Level ML Expertise: Experience managing production-level pipelines, including model deployment, monitoring, and continuous integration.
Problem Solving & Collaboration: Advanced analytical skills and a collaborative approach to solving complex challenges across teams.
Startup Mindset: Adaptability and experience in fast-paced, mission-driven environments with high levels of ambiguity.
Preferred:
Healthcare/Clinical Trials Experience: Background in working with oncology or clinical trial data.
GenAI/LLM Proficiency: Hands-on experience developing and deploying GenAI/LLM-based models and open-source frameworks for LLM applications.
Startup Experience: Previous involvement in an early-stage startup, ideally in health tech or life sciences, with a passion for high-growth projects.
At Paradigm Health, we are committed to providing equal employment opportunities to all qualified individuals. We encourage and welcome candidates from all backgrounds and perspectives to apply for our open positions. We are interested in all qualified individuals and ensure that all employment decisions are based on job-related factors such as skills, experience, and qualifications.
As published by Paradigm. Applications are handled on their site.
Skills this posting mentions
About Paradigm
Paradigm Health is rebuilding the clinical research ecosystem by creating a platform that enables equitable access to trials for all patients, while enhancing trial efficiency and reducing the barriers to participation for healthcare providers. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm Health aims to break down barriers across the trial ecosystem through one seamless infrastructure implemented at healthcare provider organizations, bringing potentially life-saving therapies to patients faster.
All 10 openings at ParadigmOne click, then it is written
Apply to Paradigm with a resume written for this role.
Queue Senior Machine Learning Engineer and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Paradigm’s form for you.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- 25 sent a week, free
- No card
- Nothing sent until you say so
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Put this to work
Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
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