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5 дней назад

Applied ML Engineer/Scientist (AI)

Формат работы
remote (только United_kingdom)/onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Applied ML Engineer/Scientist (AI): Applying and adapting foundational machine learning models to real-world drug discovery problems with an accent on molecular modeling, dataset curation, and model fine-tuning. Focus on translating partner needs into modeling strategies, evaluating applied performance, and feeding failure modes back into foundational model development.

Location: London, United Kingdom; remote or in-office work

Company

hirify.global is a public benefit company building AI-powered molecular modeling tools and production-grade platforms to support biology and accelerate drug discovery.

What you will do

  • Apply and adapt foundational machine learning models to real-world drug discovery and molecular modeling problems.
  • Curate and adapt datasets, select model architectures and objectives, and fine-tune models for scientific use cases.
  • Own the applied modeling loop from problem formulation and experimentation through evaluation and delivery.
  • Collaborate with ML researchers, software engineers, and chemistry and biology experts to translate partner needs into modeling strategies.
  • Identify practical gaps and failure modes and contribute improvements to hirify.global’s foundational models.

Requirements

  • Strong hands-on machine learning experience in biology, chemistry, drug discovery, or other real-world applications.
  • Familiarity with computational biology and chemistry datasets, tools, data formats, and workflows.
  • Strong hands-on experience with PyTorch and the scientific Python ecosystem, including NumPy, SciPy, and Pandas.
  • Experience contributing to and maintaining deep-learning codebases with strong engineering quality, reproducibility, and testing standards.

Nice to have

  • Experience collaborating with external partners or stakeholders on biological or chemical modeling and evaluation strategies.
  • A strong publication record in machine learning or life-science venues, especially for applied or translational research.
  • Experience working across machine learning, biology, chemistry, and physics in an interdisciplinary scientific environment.

Culture & Benefits

  • Opportunity to build tools used by scientists across biotech, academia, pharmaceutical, agricultural, and industrial research.
  • Significant ownership and independence from project concept through deployment.
  • Work alongside a highly specialized team in machine learning and scientific modeling.
  • Competitive salary with substantial equity ownership.

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