Job Description

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

hr@dawarconsulting.com akansha@dawarconsulting.com

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