Senior Scientist -II, ML Molecular Optimization
Listed on 2026-10-11
-
Research/Development
Data Scientist -
IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
- Full-time
- Salary Min: 109500
- Salary Max: 208500
- Workday Global Grade: 18
- Compensation: USD 109,500 - USD 208,500 - yearly
- Consult with project team to establish quantitative targets for driving optimization
- Identify suitable models to predict small molecule binding affinities for protein targets, and to predict pharmacological properties (PK parameters, etc.)
- Build predictive models for each project endpoint, and carefully benchmarking to evaluate performance and domain of applicability for each model
- Decisively identify the model that should be used for each project team query molecule, using data-driven approaches that take account of model uncertainty and heteroscedasticity
- Clearly communicate to the project team the rationale for model selection and why the selected models are best suited for the task at hand
- Deploy models to ensure accessibility for the project team, facilitating collaborative ideation and optimization
- Senior Scientist I:
Degree in relevant field (chemistry / computer science / machine learning / cheminformatics / chemical engineering) with experience developing machine learning models related to chemical and biological data (10+ years of experience for BS, 8+ years for MS, 0+ years for PhD). Leveling will be commensurate to experience. - Senior Scientist II:
Degree in relevant field (chemistry / computer science / machine learning / cheminformatics / chemical engineering) with experience developing machine learning models related to chemical and biological data (12+ years of experience for BS, 10+ years for MS, 4+ years for PhD). Leveling will be commensurate to experience. - Expertise with developing, implementing and deploying programs and computational solutions employing Machine Learning/Deep learning and Cheminformatics
- Expertise in AI/ML-enabled molecular generation, pose prediction, affinity prediction and/or prediction of pharmacological properties (e.g. PK)
- Strong programming skills in Python and experience with data science stack including numpy, pandas, scikit-learn, and other related scientific libraries
- Ability to implement, debug, and maintain computational tools in common programming languages (Python, etc…) and proficiency with cloud computing capabilities
- Familiarity with modern deep learning architectures including GNN, CNN, RNN, Transformer, GCNN and MPNN, and machine learning paradigms such as generative models, GAN, and active learning
- Strong analytical and problem-solving skills with demonstrated ability to think critically and creatively, and provide solutions both individually and collaboratively with internal experts
- Excellent ability to communicate clearly and concisely with colleagues and collaborators including an ability to explain complex ideas to non-specialists
About Abb Vie
Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at .
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This position brings an opportunity to make innovative contributions that will define how Abb Vie leverages AI-enabled drug discovery across our small molecule portfolio. The key responsibilities of this position are to identify, develop, optimize, validate, and deploy innovative machine learning approaches to guide molecular optimization. This role will collaborate closely with project teams comprising medicinal chemists, structural biologists, biochemists, cell biologists, and other computational chemistry / chemo informatics experts.
Responsibilities:
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law:
The compensation range described below is the range of possible base pay compensation that the Company believes ingood faith it will pay for this role at the timeof this posting based on the job grade for this position.
Individual compensation paid within this range will depend on many factors including geographic location, andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture.
We offer a comprehensive package of benefits including paid time off (vacation, holidays,…
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