Principal Medicinal Chemist

About Deep Origin Deep Origin is a biotechnology company building an operating system for science that transforms how life science research is conducted. Our AI-powered platforms simulate biology, streamline R&D workflows, and enable scientists to model complex biological systems at scale. As part of strategic government-backed initiatives and the expansion of our AI-driven simulation infrastructure, we are scaling our capabilities in whole-human modeling and predictive toxicology. Exceptional modeling talent is a critical lever in accelerating our mission to reduce disease and extend human healthspan. About the Role We are seeking a Principal Medicinal Chemist to lead and advance small-molecule drug discovery programs from early hit identification through development candidate selection. This is a senior, hands-on scientific leadership role requiring deep expertise in medicinal chemistry, strategic thinking, and cross-functional collaboration. This position calls for a highly creative and experienced chemist who can independently design and execute medicinal chemistry strategies while contributing to the integration of computational and AI-driven approaches into drug discovery workflows. The ideal candidate will combine strong technical depth with the ability to guide internal teams and external partners toward impactful outcomes. Requirements Must-Have - PhD in Organic Chemistry or a related field with 3-8 years of industry experience (or MS with 5-10 years, BS with 8-15 years) in medicinal chemistry - Proven track record of advancing drug discovery programs through key milestones (Hit-to-Lead and Lead Optimization) - Deep expertise in synthetic organic chemistry, including modern methods and reaction mechanisms - Strong experience in structure-based and ligand-based drug design - Demonstrated ability to optimize compounds for potency, selectivity, and DMPK/safety properties - High level of creativity, productivity, and independent problem-solving ability - Experience managing external CROs and collaborating across disciplines - Excellent English communication skills with the ability to clearly present complex scientific concepts - Experience working remotely with international teams. Nice-to-Have - Experience integrating computational chemistry, machine learning, or AI-driven design into medicinal chemistry workflows - Background in predictive toxicology or ADMET modeling - Prior experience contributing to IND-enabling studies or clinical candidate selection - Familiarity with modern data science tools and cheminformatics platforms. Key Responsibilities - Propose and independently drive medicinal chemistry strategies to progress programs from hit identification through lead optimization to development candidate selection - Lead chemistry efforts within cross-functional project teams – computational scientists, biologists, and ML engineers - Design novel compounds using structure-based and ligand-based approaches to optimize potency, selectivity, and drug-like properties - Analyze SAR data and guide iterative design cycles to find a balance between potency, selectivity, and physico-chemical properties - Contribute to and integrate AI-driven and computational modeling insights into compound design strategies - Serve as a technical leader and mentor for internal chemists and external collaborators - Manage external CRO partnerships to ensure high-quality and timely delivery of chemistry objectives - Author and contribute to patent applications, scientific publications, and internal reports. Values & Cultural Alignment - Operates with ownership and urgency in ambiguous scientific environments - Communicates complex modeling concepts with clarity and precision - Thrives in cross-disciplinary collaboration between science and engineering - Approaches scientific challenges with intellectual rigor and curiosity - Balances research depth with practical execution toward milestone delivery Why This Role Matters Now Deep Origin is at a pivotal moment in scaling its AI-driven platform to transform drug discovery. As we expand into whole-human modeling and predictive toxicology, medicinal chemistry plays a critical role in translating computational insights into real-world therapeutic candidates. This role sits at the intersection of cutting-edge AI and traditional drug discovery, offering the opportunity to redefine how medicines are designed—faster, more efficiently, and with greater precision than ever before.