Overview

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.

Responsibilities:
  • 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
Required Qualifications:
  • 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
Benefits:
  • 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.
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.
Technologies:
  • Python
  • Git
  • NumPy
  • SciPy
  • Pandas
  • PyTorch
  • C/C++
  • Julia
  • RDKit
  • OpenMM
  • GROMACS
  • AMBER
  • LAMMPS
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