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.