Unlearn

Applied Machine Learning Scientist

Unlearn San Francisco, California, United States · $140K–$165K/yr

Research Services · 51-200 employees

Yesterday
machine-learning Mid (2-5 yrs) Full-time United States
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About the role

Design and implement machine learning models to characterize and predict disease progression using real-world clinical data. Communicate technical findings to stakeholders and stay current with ML developments to represent the company in the scientific community.

What they look for

Machine learning Python Data science Software engineering Predictive modeling Clinical data analysis Digital twins Probabilistic modeling Unsupervised ML EBM NLP LLM Optimization theory Reinforcement learning AWS Clinical research

Requirements

Requires a bachelor's degree in a technical field and at least 2 years of experience developing machine learning models. Candidates must demonstrate software engineering competency and proficiency in the Python data science ecosystem.

Benefits

Meaningful equity participation 100% company-covered medical insurance 100% company-covered dental insurance 100% company-covered vision insurance 401k plan with matching Flexible PTO Company holidays Annual company-wide break Commuter benefits Paid parental leave

Full description

Our Mission and Vision

Unlearn exists to transform clinical development by making every trial smarter. We harness data, AI, and digital twins to enable faster, more robust studies that bring life-saving treatments to patients faster. This mission drives everything we do as we partner with biopharmaceutical companies to redesign how clinical trials are planned, run, and analyzed.

We are defining the future of clinical development with unmatched scientific credibility, replacing uncertainty with AI-powered precision so decisions are clearer and trials are stronger. We don’t just disrupt the pharmaceutical industry, we create lasting change.

We believe AI will define the future of medicine, and we are committed to building that future responsibly, rigorously, and in close collaboration with our partners in clinical development.

About Our Team

We come from a variety of backgrounds ranging from machine learning to marketing—but regardless of where we come from, Unlearners share some common traits:

  • Unlearners are ambitious; we aren’t intimidated by big, challenging goals.
  • Unlearners are disciplined experimenters; we break down our big goals into smaller chunks and meet as often as necessary to track our velocity and iterate quickly.
  • Unlearners are gritty; we never give up, setbacks just make us try harder.
  • Unlearners are receptive to new ideas; in fact, we hate being stuck with the status quo
  • Unlearners are storytellers; sharing information with each other and with the world is super important, too important to be boring. And, last but not least,
  • Unlearners are team-oriented; we put the mission first, the company second, the team third, and individuals last.

Headquartered in San Francisco, Unlearn was founded in 2017 by a team of world-class machine learning scientists. We have raised venture capital from top tier investors such as Altimeter, Insight Partners, Radical Ventures, 8VC, DCVC, and DCVC Bio, and completed our $50 million Series C in January 2024.

If our purpose and culture resonate with you, we invite you to apply.

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
  • 401k plan with matching
  • Flexible PTO plus company holidays
  • Annual company-wide break December 24 through January 1
  • Commuter benefits
  • 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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