Product Research Scientist, Drug Discovery
Job Description:
- 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