Senior Scientist II (Computational Chemistry)

Location: Alameda, California, United States; office-based

Base salary: $149,000–$188,000 per year

Company

hirify.global develops medicines and supports small-molecule drug discovery programs.

What you will do

• Apply ligand- and structure-based computational methods to small-molecule discovery programs.
• Plan, execute, analyze, and communicate molecular dynamics simulations and free-energy calculations for compound prioritization and molecular design.
• Use molecular docking, protein–ligand interaction analysis, conformational analysis, similarity searching, and virtual screening to generate experimentally testable hypotheses.
• Analyze compound collections, structure–activity relationships, chemical diversity, and virtual libraries using cheminformatics methods.
• Evaluate and develop machine-learning models for molecular property and activity prediction, including scientifically appropriate validation and uncertainty assessment.
• Integrate computational results into discovery workflows and collaborate with medicinal chemists, structural biologists, biologists, pharmacologists, and bioinformatics scientists.

Requirements

• Bachelor’s degree in a related discipline and at least 9 years of relevant experience; or a master’s degree and at least 7 years; or a PhD in Computational Chemistry, Cheminformatics, or a related discipline with at least 2 years of relevant biotechnology or pharmaceutical industry experience; equivalent combinations may qualify.
• Strong foundation in molecular modeling and the physical principles governing protein–ligand interactions.
• Hands-on experience with one or more structure-based drug-design methods, including molecular docking, molecular dynamics, free-energy calculations, conformational analysis, or protein–ligand interaction analysis.
• Proficiency in Python for scientific computing, data analysis, or computational workflow development.
• Working knowledge of cheminformatics concepts, including molecular representations, fingerprints, descriptors, similarity and substructure searching, clustering, or compound-library analysis.
• Ability to critically analyze computational and experimental data and translate results into clear, testable molecular-design hypotheses.
• Strong written, oral, and presentation communication skills, with the ability to work effectively across scientific disciplines.
• Scientific curiosity and willingness to learn new methods as program needs and technologies evolve.

Nice to have

• Familiarity with RDKit, OpenMM, GROMACS, AMBER, or comparable open-source cheminformatics and molecular-modeling platforms.
• Experience applying computational and machine-learning approaches to practical drug-discovery problems.

Culture & Benefits

• Interdisciplinary, collaborative research environment with close cross-functional scientific collaboration.
• Modern office with collaborative workspace, dual monitors, and ergonomic chairs.
• 401(k) plan with company contributions, medical, dental and vision coverage, life and disability insurance, and flexible spending accounts.
• Discretionary annual bonus, company stock purchase opportunities, and long-term incentives.
• Fifteen accrued vacation days in the first year, 17 paid holidays including a December winter shutdown, and up to 10 sick days annually.