Product Research Scientist at SandboxAQ translating scientific research into production-ready software solutions. Collaborating with ML and computational chemistry teams for drug discovery efforts.
Responsibilities
Partner with ML and Computational Chemistry researchers to translate internal scientific code and prototypes into robust, production-ready software systems for external product offerings.
Implement and integrate core scientific algorithms (ML, deep learning, physics-based simulation) into scalable product platforms.
Collaborate within a multi-disciplinary "pod" of engineers, computational chemists, AI experts, and product managers to define requirements, architecture, and deployment strategies for new features.
Ensure the scientific integrity and accuracy of research models (e.g., active learning, FEP, etc.) when deployed in production.
Drive the product lifecycle from scientific inception to external deployment, ensuring technical excellence and market fit.
Requirements
PhD in chemistry, biology, or a related discipline.
3-5 years of relevant experience in a product-focused engineering or applied science role, specifically translating ML or computational chemistry research into production software in the private sector (biotech/pharma preferred).
Experience deploying and maintaining machine learning models for scientific applications (e.g., molecular property prediction, multi-objective optimization).
Proficiency with Python toolkits for scientific computing (e.g., NumPy, Pandas, SciPy) and machine learning (e.g., scikit-learn, PyTorch).
Strong communication skills and a drive to collaborate with colleagues to identify problems and communicate technical solutions in an accessible manner.
Benefits
Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions
Retirement savings with company matching
Paid parental leave
Inclusive family-building benefits
Fully remote
Flexible paid time off
Company-wide seasonal breaks
Support for flexible work arrangements that enable sustainable performance
Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs
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