About the role

  • Machine Learning Engineer managing projects deploying techniques for molecular optimization in diagnostics and life sciences. Focused on engineering pipelines for probabilistic predictions and Bayesian acquisition.

Responsibilities

  • Manage projects deploying new techniques for machine learning-based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns.
  • Focus on engineering pipelines for probabilistic molecular property prediction and Bayesian acquisition for active learning-based drug discovery.
  • Additional activities may extend to include engineering pipelines for molecular generative modeling.

Requirements

  • PhD in a quantitative field (e.g., Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS with 3+ years of industry experience.
  • Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases).
  • Significant experience in at least one of the following areas: Molecular property prediction, Probabilistic modeling/inference, Bayesian optimization or active learning, Production software engineering or pipeline optimization, Cheminformatics.
  • Strong software engineering experience is required.

Benefits

  • Medical
  • Dental
  • Vision
  • Paid Sick leave
  • 401K

Job title

Machine Learning Engineer

Job type

Experience level

Mid levelSenior

Salary

$78 per hour

Degree requirement

Postgraduate Degree

Tech skills

Location requirements

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