Senior R&D Engineer

Deep Origin is a biotech startup building an operating system for science that transforms how life science research is conducted. Led by Michael Antonov, co-founder of Oculus, and backed by Formic Ventures, we are redefining the infrastructure behind modern drug discovery. Our AI-driven platform enables scientists to accelerate discovery, reduce cost, and bring breakthrough innovations to life faster. As we scale, overall excellence is a critical lever in advancing our mission to dramatically reduce disease and extend human healthspan.

We are seeking a Senior Scientific Software Engineer [Macromolecular Modeling] to join our international team of talented scientists, software engineers, and ML researchers to design and implement new methods for macromolecular modeling and drug discovery, and to seek solutions that advance scientific problems through innovation and rigorous method development. You will work at the intersection of computational chemistry, structural biology, and modern machine learning, contributing to a platform that directly shapes how novel therapeutics are discovered and advanced.

• Design and implement scalable algorithms for preparation, analysis and modeling of macromolecular systems that advance the development of novel therapeutics.
• Develop and translate complex scientific workflows into robust, production-grade software, enabling scientists across the platform to run advanced modeling tasks without engineering bottlenecks
• Collaborate with ML researchers, computational chemists, and software engineers to integrate novel generative and predictive models into the core platform, expanding its capacity to address unsolved drug discovery challenges
• Identify and close gaps between cutting-edge academic methods and platform capabilities, evaluating emerging tools and techniques and driving their adoption where they deliver meaningful scientific value 
• Contribute to a culture of engineering excellence through rigorous code review, mentorship, and the establishment of best practices that raise the quality bar across the scientific software team

Must-Have

• Senior-level software engineering experience with strong proficiency in Python (5+ years) in the industry and modern object-oriented programming
• Demonstrated command of software development best practices, including version control (Git), unit and integration testing, code review, and continuous integration/deployment
• Proven ability to design, build, and maintain robust, scalable, and well-documented scientific software
• Strong problem-solving skills, with the ability to translate complex scientific challenges into clean, maintainable code
• Excellent communication, collaboration, and presentation skills, with the ability to work effectively in a cross-functional, international team of scientists, engineers, and ML researchers

Nice-to-Have

• Scientific background (MS or PhD) in computational chemistry, structural biology, biophysics, computer science, physics, molecular modeling or a closely related discipline
• Hands-on experience developing or applying methods such as molecular dynamics, free energy calculations, molecular docking, protein structure prediction, generative models for biomolecular design or machine learning approaches to biomolecular systems 
• Familiarity with scientific Python libraries (such as NumPy, SciPy, Pandas, etc.) and modern ML frameworks (PyTorch, etc.) 
• Experience with GPU computing and high-performance computing environments
• Knowledge of additional programming languages such as C/C++, or Julia 
• Experience working with established molecular modeling toolkits (e.g., RDKit, OpenMM, GROMACS, AMBER, LAMMPS) 
• Track record of contributing to open-source scientific software or to collaborative, multi-disciplinary research projects 
• Prior experience in a drug discovery setting, whether in academia, biotech, or pharma. 

• Ownership mindset – you take responsibility for building and improving things. 
• Comfortable navigating ambiguity in a fast-moving startup environment.
• Strong collaborator who partners effectively with cross-functional teams.
• Pragmatic and impact-driven, focused on building solutions that scale with the organization.

• Health insurance for you and your family.
• Additional leave days added to your annual paid time off.
• Weekly highly specialized seminars on bio-machine learning and chemistry.
• Collaborating with highly experienced professionals.