Group Leader, Machine Learning

Posted 23 Days Ago
Be an Early Applicant
South San Francisco, CA
Senior level
Biotech
The Role
As a Machine Learning Group Leader, you will manage a team to develop predictive models for epigenetic reprogramming, collaborating with experimental scientists. You will lead algorithm development and contribute significantly to decision-making within the company, while also engaging in coding and documentation.
Summary Generated by Built In

Company info

NewLimit is a biotechnology company working to radically extend human healthspan. We’re developing medicines to treat age-related diseases by reprogramming the epigenome, a new therapeutic mechanism to restore regenerative potential in aged and diseased cells. We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.

Description

NewLimit is recruiting a Machine Learning Group Leader to lead our Predictive Modeling team. Our team is developing models to predict the effect of epigenetic reprogramming perturbations on cell state & function in silico, powered by the world’s largest data corpus of reprogramming experiments. These models are an essential component of our Discovery Engine, allowing us to search efficiently through the massive space of epigenetic reprogramming hypotheses.

Your role will focus on improving these models & developing new methods to accelerate the pace of NewLimit’s therapeutic discoveries.

As the Group Leader of our Predictive Modeling team, you will:

  • Lead, recruit, and manage a team of Machine Learning Scientists & Engineers
  • Guide the development of algorithms & machine learning models to solve problems at the core of our business
  • Develop in silico models of cell reprogramming atop a massive data corpus
  • Collaborate with experimental scientists to test in silico predictions in the real worlds every month
  • Plan roadmaps and manage budgets for the Predictive Modeling group.
  • Contribute to company-wide decision making.
  • Write code. Document APIs. Commit every week. At NewLimit, everyone contributes to the execution of our plans.

Requirements

  • Experience performing research in machine learning — may be demonstrated through a Ph.D., or equivalent outcomes from industry experience
  • Demonstrated history of solving problems in the natural sciences with machine learning — this might be demonstrated with public code repositories, scientific publications, or impressive blog posts
  • Experience building robust software to enable reproducible experimentation
  • Experience working alongside experimental scientists

Nice to have

  • Experience recruiting & managing a technical team
  • Experience contributing to cell and gene therapy products
  • Experience with single cell genomics data, algorithms, and experimental design
  • Familiarity with Bayesian optimization, out-of-distribution prediction models, and biological sequence modeling
  • Experience with cloud computing, high performance computing, and general DevOps

Benefits

NewLimit offers generous benefits to ensure our team can focus on our mission:

  • Health, dental, and vision insurance
  • 401(k) with company match
  • Paid parental leave
  • Industry-leading paid time off (PTO) — 20 days/year for all employees + holidays
  • Meals and snacks on-site

Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Learn more at: https://www.newlimit.com/careers   *This compensation and benefits information is based on Company's good faith estimate as of the date of publication and may be modified in the future.



Top Skills

Machine Learning
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The Company
HQ: South San Francisco, CA
18 Employees
On-site Workplace
Year Founded: 2022

What We Do

NewLimit is a biotechnology company working to radically extend human healthspan. We’re developing medicines to treat age-related diseases by reprogramming the epigenome, a new therapeutic mechanism to restore regenerative potential in aged and diseased cells. We leverage functional genomics, pooled perturbation screening, and machine learning models to unravel the biology of epigenetic aging and disease using experiments of unprecedented scale.

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