Senior Computer-Aided Drug Design (CADD) Software Developer
About Chemify
Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world’s largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity.
Job Description:
We seek a talented and motivated Senior Computer-Aided Drug Design (CADD) Software Developer to build and enhance our next-generation platform.
You’ll be joining a dynamic, cross-disciplinary team of computational scientists, chemists, medicinal chemists, software engineers, data engineers, and AI researchers dedicated to accelerating the discovery of new molecules.
We are in a fast-paced, innovative environment, and our product roadmaps are delivered in tight iterations. To be successful in this role, you’ll be comfortable tackling complex scientific challenges and collaborating closely to create powerful, intuitive tools for drug design and beyond.
Our software and robotic platforms empower scientists to design, analyze, and optimize novel therapeutic candidates through advanced computational tools and make them for real in our automated robotic-assisted synthesis platform. You will develop and integrate cutting-edge CADD methodologies, from molecular modelling and simulation to machine learning-based tools, into a cohesive and user-friendly application suite. We are using an API-first architecture, and you’ll need a deep understanding of scientific software development, a user-centric mindset, and proficiency in Python, C++, CUDA and relevant cheminformatics toolkits.
If you are passionate about solving complex problems at the intersection of chemistry, computer science, and medicine and are energized by working with scientists to create tools that make a real-world impact, we’d love to have you join our team.
Key Responsibilities:
- Collaborate with a cross-disciplinary team of computational chemists, chemists, medicinal chemists and AI/data scientists to translate complex scientific requirements into robust and impactful software features.
- Own the full lifecycle of feature development, from conceptualization and algorithm implementation to building intuitive user interfaces and deploying scalable backend services.
- Design, develop, and maintain software for molecular modelling, virtual screening, molecular dynamics, and predictive modelling (QSAR/ML).
- Collaborate with the Infrastructure team to ensure computational workflows are optimized for performance, scalability, and cost-effectiveness on cloud and HPC environments.
- Champion best practices for scientific software development, including rigorous testing, validation, code documentation, and ensuring the reproducibility of computational results.
- Mentor junior colleagues and share your knowledge of CADD, cheminformatics, and software engineering with the wider team.
- Contribute to team-wide initiatives, including code reviews, design discussions, and evaluating new computational methods and technologies.
What you’ll bring:
- MSc or PhD, or equivalent experience, in Computational Chemistry, Cheminformatics, Physics, Biophysics, Computer Science, or a related field with a strong focus on molecular modelling, molecular understanding, or related computational approaches across chemistry and life sciences.
- 5+ years of commercial or academic software engineering experience, preferably in a scientific or drug discovery context.
- Deep proficiency in Python and extensive experience with scientific computing and data science libraries (e.g., NumPy, SciPy, Scikit-learn).
- Proficiency in C/C++ for developing or integrating high-performance computational chemistry algorithm.
- Experience with parallel programming and GPU acceleration using CUDA for scientific computing applications.
- Experience building scalable and robust backend services and APIs using modern Python frameworks, particularly FastAPI.
- Hands-on experience with core cheminformatics toolkits such as RDKit.
- Proven experience building user-facing applications or components, with a strong interest in UI/UX for scientific software. Experience with modern web frameworks React is highly desirable.
- Knowledge of relational databases (e.g., PostgreSQL) and experience writing complex SQL queries for scientific data.
- Familiarity with cloud computing environments (AWS/GCP/Azure), especially services related to batch processing, data storage, and high-performance computing (HPC).
- Proven ability working with containerized applications (Docker) and an understanding of CI/CD principles.
Beneficial Skills:
- Practical experience with molecular modelling software and libraries (e.g. OpenMM, GROMACS, MDAnalysis, PyMOL).
- Experience applying machine learning (especially deep learning, GNNs, or generative models) to chemical or biological data.
- Knowledge of advanced CADD techniques such as Free Energy Perturbation (FEP), docking, pharmacophore modelling, or quantum mechanics (QM).
- Familiarity with DevOps practices and Infrastructure as Code tools (e.g., AWS CDK, Terraform).
- A portfolio of projects or open-source contributions demonstrating your skills in scientific software development.
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