Machine Learning Engineer

Our client, a world
leader in diagnostics and life sciences, is looking for a "Machine
Learning Engineer” based out of South San Francisco, CA (Hybrid).

Job Duration: Long term
Contract (Possibility Of Further Extension)

Pay Rate : $78/hr on W2
DOE

Company Benefits:
Medical, Dental, Vision, Paid Sick leave, 401K

We are looking for
talented Machine Learning Engineer to join Prescient Design, a division
devoted to developing structural and machine learning -based methods for
molecular design within client’s Research and Early Development (gRED)
organization. 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 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).
  
• For this role, we are seeking candidates with significant experience in at
  least one of the following areas, and ideally some experience in one or more of
  the others, listed in order of importance: Molecular property prediction,
  Probabilistic modeling/inference, Bayesian optimization or active learning,
  Production software engineering or pipeline optimization, Cheminformatics. In
  addition to these skills, strong software engineering experience is required.
  

If interested, please
send us your updated resume at

[email protected]/[email protected]