
location_onMayor's Walk, Beacon Hill, Boston, Suffolk County, Massachusetts, 02108, United States
Deep Origin is 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.
We are now building the next-generation platform for predicting drug toxicity in silico, transforming how pharmaceutical companies evaluate safety before clinical trials. Our mission is to reduce failure rates, accelerate drug development, and eliminate unnecessary animal testing through high-fidelity computational models of human biology.
We are not building incremental QSAR tools. We are building foundational infrastructure for predictive toxicology in the age of AI, systems biology, and large-scale computation.
We are seeking an experienced and highly strategic VP/SVP of Drug Discovery to lead and scale our discovery organization. This is a critical executive leadership role for a hands-on scientific leader who has spent significant time navigating the realities of drug discovery and development — someone who understands not only what can work scientifically, but what actually translates into successful therapeutic programs.
This individual will serve as a key scientific and operational leader inside the company, partnering closely with computational scientists, experimental scientists, platform teams, translational biology, external collaborators, and executive leadership to prioritize programs, guide strategic decisions, and accelerate pipeline execution.
This is not a purely managerial role. We are looking for someone who remains deeply engaged in scientific reasoning, program review, experimental strategy, and portfolio decision-making. The role is ideal for a senior biotech leader who wants to help build a next-generation AI-enabled discovery organization from the ground up while directly influencing the future direction of therapeutic development.
Deep Origin is entering a phase where scientific innovation, platform infrastructure, and commercial partnerships must scale simultaneously. This role will help shape how we translate cutting-edge computational capabilities into real drug discovery outcomes — guiding portfolio decisions, advancing programs toward the clinic, and building the foundation of a next-generation discovery organization.
We value leaders who are comfortable navigating ambiguity in a fast-moving, high-impact environment. We seek strong collaborators across science, engineering, and business teams who are pragmatic yet ambitious — focused on building category-defining systems, not incremental improvements.
Join us to define the future of drug safety and predictive toxicology. We offer a competitive compensation package with meaningful equity, comprehensive health, dental, and vision coverage, and a remote-friendly culture with optional onsite work. We also host annual team gatherings and company events to foster connection.
Work model: Hybrid
Mayor's Walk, Beacon Hill, Boston, Suffolk County, Massachusetts, 02108, United States
Boston, Massachusetts
Experience in AI-enabled drug discovery, computational biology, systems pharmacology, or platform biotech environments. Background working with data-driven discovery approaches and computational infrastructure. Experience across multiple therapeutic areas and modalities. Familiarity with translational biomarkers, precision medicine strategies, and clinical development planning. Experience building discovery organizations or scaling R&D teams within startup environments. Prior experience interacting with regulatory agencies, KOLs, or strategic pharma partnerships. Entrepreneurial or venture-backed biotech experience.
Skills: Drug Discovery, Drug Development, Target Identification, Hit Discovery, Lead Optimization, Translational Strategy, Clinical Transition, Preclinical Development, Clinical Development, Computational Biology.
Education: PhD, MD, or equivalent advanced scientific degree in biology, pharmacology, chemistry, immunology, translational medicine, or related field.