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Applied Machine Learning Scientist

Full-time On-site San Francisco, California, United States

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Every day, people are waiting for a diagnosis, for a treatment, for a chance. Our mission is to help life-saving treatments reach patients faster.

About the role

Our Mission
Every day, people are waiting for a diagnosis, for a treatment, for a chance. Our mission is to help life-saving treatments reach patients faster.
That isn’t an abstraction to us. It’s the reason Unlearn exists, and it’s why the pace and rigor of our work matter so much.
What We Do
Unlearn is transforming clinical development by making every trial smarter. We partner with biopharmaceutical companies to redesign how clinical trials are planned, conducted, and analyzed. We use data, AI, and digital twins to make studies faster and more robust.
A digital twin is a comprehensive prediction of a patient’s expected outcomes under a defined standard of care. It is generated by machine learning models built on our proprietary technology. Leading pharma and biotech companies trust us to deliver scientifically rigorous work on studies where the stakes are high and the timelines impact patients.
Where We’re Going
Our goal is to become the gold standard for AI-driven clinical development. Getting there takes disciplined execution and data, models, and AI that is implemented with partners using a strong engineering foundation that holds up in a regulated, compliance-heavy environment. We’re building durable advantages rooted in science and innovative technologies, and that foundation is what will make our leadership last.
Our Values
Accountability, Agility, and Acceleration describe how we work with each other every day. Fulfilling our mission depends on all of us doing our best work, and it’s on all of us to build and protect the culture that makes that possible.
Accountability: We own outcomes, not just tasks
We take responsibility for results, make decisions with urgency, and follow through on our commitments. When things don’t go as planned, we say so. We surface issues early, learn, iterate quickly, and move forward without blame. We give and receive feedback that is clear, direct, and actionable.
Agility: We follow the evidence
Drug development and AI evolve rapidly. We stay curious, embrace new information, and change course when the evidence changes. We keep a close eye on where the industry is heading and build technology flexible enough to adapt when new data or opportunities arise. We value speed of learning over being right.
Acceleration: We create momentum
Our mission is to accelerate the development of new medicines, and that starts with how we work. We simplify, prioritize, and execute with urgency. Unlearners own the problems in front of them and are empowered to solve them. That helps our customers, our teammates, and our company move faster without sacrificing scientific rigor.
About Unlearn
Unlearn was founded in 2017 by a team of world-class machine learning scientists and is headquartered in San Francisco. We’re backed by top-tier investors including Altimeter, Insight Partners, Radical Ventures, 8VC, and DCVC. We have substantially advanced AI technology for clinical trials, including regulatory-grade applications, and are embedded in multiple clinical trials with top Pharma and Biotech companies.
Applied ML Scientists lead Unlearn’s work to develop state-of-the-art ML approaches for generating Digital Twins – probabilistic models of a patient’s future health outcomes given knowledge of their current and past medical history. Applied ML Scientists at Unlearn come from a wide range of disciplines, and have honed their ML expertise through their previous experience conducting novel and impactful research at top academic and industrial labs or their previous work delivering ML and data-science products in highly ambiguous and challenging commercial settings. Successful Applied ML Scientists at Unlearn are entrepreneurial in their approach; feeling a strong sense of end-to-end ownership of their mission, they investigate broadly to find the right tools and techniques to help their teams succeed. They are also highly determined individuals, powering through problems with cleverness and resolve.
Responsibilities include:
• Design and implement machine learning models to characterize and predict disease progression.
• Apply and fine-tune proprietary architectures to real-world clinical data.
• Clearly communicate technical findings and results to internal and external stakeholders.
• Stay up to date with developments in the ML field to inform Unlearn’s modeling work.
• Represent Unlearn to the broader scientific community.
Minimum requirements:
• B.S. in computer science or engineering, physics, mathematics, or a related field.
• 2+ years of experience developing machine learning models and adapting them to solve real-world problems.
• Demonstrable competency in the fundamentals of software engineering.
• Fluency in the Python machine learning and data science ecosystem.
• Evidence of successful execution of ML projects in an academic or industrial setting.
• A track record of intellectual curiosity - e.g., exploring new techniques, tools, or ideas independently.
Bonus points for:
• Contributions to well-known open-source ML tools or frameworks.
• Previous experience with unsupervised ML, EBM, NLP, LLM, optimization theory, or reinforcement learning.
• Prior experience working with healthcare or clinical machine learning applications.
• Familiarity with AWS cloud computing services.
Benefits & Perks
The following benefits and perks are for full time roles only.
• Meaningful equity participation
• 100% company-covered medical, dental, & vision insurance plans for you and your dependents
• 401(k) plan with matching
• Flexible PTO plus company holidays
• Annual company-wide break December 24 through January 1
• Commuter and Wellness benefits
• Tech stipend
• Paid Parental Leave
Unlearn is an equal opportunity employer.
At Unlearn, we are committed to building a diverse and inclusive workplace, because inclusion and diversity are essential to achieving our mission. If you’re excited about this role, and your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply nevertheless.

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