- Company Name
- deepmirror
- Job Title
- Research Engineer
- Job Description
-
Job Title: Research Engineer
Role Summary: Design, develop, and deploy advanced AI and physics‑based algorithms for structure‑based drug design (SBDD), integrating them into a production platform that serves computational and medicinal chemists globally.
Expectations:
- Deliver production‑ready models and software that predict ligand‑target binding with deep learning and physics‑based methods.
- Own end‑to‑end development cycles, from algorithm research to scalable deployment.
- Collaborate closely with cross‑functional teams to translate scientific needs into user‑centric solutions.
- Support users, gather feedback, troubleshoot, and iterate on product features.
- Present research outcomes through publications, technical documents, and conferences.
Key Responsibilities:
- Research and implement state‑of‑the‑art structure‑prediction algorithms for drug discovery.
- Build, test, and maintain high‑quality Python code using scientific computing and deep‑learning frameworks.
- Integrate molecular docking, scoring, and molecular‑dynamics simulation tools into the platform.
- Deploy machine‑learning models into production, ensuring scalability, robustness, and maintainability.
- Work with internal and external stakeholders to understand workflows, capture requirements, and provide technical guidance.
- Document algorithms, system architecture, and research findings for both technical and non‑technical audiences.
Required Skills:
- PhD, Postdoc, or equivalent industry experience in Structure‑Based Drug Design.
- Deep expertise in deep learning for SBDD (e.g., graph neural networks, transformer‑based models).
- Proficiency in Python, scientific libraries (NumPy, SciPy), deep‑learning frameworks (PyTorch, TensorFlow), and version control (Git).
- Hands‑on experience with molecular docking (e.g., AutoDock), scoring functions, and molecular‑dynamics simulations (e.g., OpenMM, GROMACS).
- Strong software engineering practices: modular design, unit testing, continuous integration, and performance profiling.
- Excellent written and verbal communication skills for technical and non‑technical audiences.
- Collaborative mindset and ability to work in interdisciplinary, high‑performing teams.
Required Education & Certifications:
- PhD (or equivalent) in Chemistry, Biochemistry, Computational Biology, Bioinformatics, Computer Science, or related field.
- Advanced coursework or proven experience in machine learning, statistics, chemical informatics, or physics‑based modeling.
Nice to Have (not mandatory):
- Peer‑reviewed publications on protein–ligand binding, protein co‑folding, or computational drug discovery.
- Experience deploying ML models in production environments (cloud, Docker, Kubernetes).
- Contributions to open‑source scientific software (RDKit, OpenMM, PyTorch, etc.).