Overview
On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
No Travel Required
Skills
Biology
Chemical Engineering
Active Learning
Machine Learning (ML)
PyTorch
Workflow
Optimization
Job Details
Job Title: Machine Learning Engineer
Location: South San Francisco, CA - Hybrid
Duration: 12 months
Description
- We are looking for talented Machine Learning Engineers to join Prescient Design, a division devoted to developing structural and machine learning based methods for molecular design
- The successful candidate will 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.
- Special focus will be given to 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.
Qualifications:
- PhD degree in a quantitative field (?e.g.?, Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience.
- Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases)
- Record of achievement, including at least one high-impact first author publication or equivalent.
- Excellent written, visual, and oral communication and collaboration skills.
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