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© All Rights Reserved. ApplyBlast.com
SandboxAQ
The Machine Learning Scientist will own machine learned force fields for the PFAS substitution program, generating first principles data and training models to predict molecular properties. This role involves designing high-throughput simulation campaigns, building data generation infrastructure, and deploying potentials for semiconductor material screening. The scientist will collaborate across teams to ensure accurate property predictions and extend model coverage to relevant process chemistries.
Headquarters
Palo Alto, California, United States
Company Size
51-200 employees
Founded
2021
SandboxAQ builds AI and advanced-computing solutions that combine large-scale AI, simulation, and next‑generation computing (including quantum-aware techniques) to solve complex scientific, security, and sensing problems. Its product suite includes AI simulation platforms (AQBioSim, AQChemSim, AQMed), large quantitative models, AI sensing and navigation (AQNav), and cryptography and cybersecurity tools such as AQtive Guard for quantum-safe key management. SandboxAQ serves global organizations across research, defense, and enterprise markets and supports education and knowledge sharing through residencies, scholarships, and a publications library.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for SandboxAQ.
12% above the average for this role
Force Field Scientist
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