Director of Clinical Pharmacology (AI)

Location: Cambridge, Massachusetts, with hybrid attendance required 3 days per week

Company

hirify.global applies frontier AI and machine learning to drug discovery, developing predictive and generative models for designing medicines across multiple therapeutic areas and modalities.

What you will do

• Lead clinical pharmacology, bioanalysis, and modeling strategies for oncology and non-oncology small-molecule programs from Phase 1 through late-stage development.
• Design and execute Phase 1 and 2 clinical pharmacology activities, including dose escalation, dose rationale, PK sampling, food-effect, and drug-drug interaction assessments.
• Manage global CROs and external vendors delivering clinical pharmacology studies, bioanalysis, and PK analyses.
• Direct interpretation of clinical PK and human AME data using PopPK and exposure-response modeling to support dose and RP2D selection.
• Author and review clinical pharmacology and biopharmaceutics sections for INDs, CTAs, IBs, CSRs, NDAs, and MAAs, and represent the company in regulatory meetings.
• Apply predictive AI, mechanistic PK, allometric scaling, and PBPK modeling to improve human dose prediction, DDI assessment, and translational development.

Requirements

• Ph.D. or Pharm.D. in Pharmacokinetics, Clinical Pharmacology, Pharmaceutical Sciences, or a related discipline.
• 8+ years of relevant biopharmaceutical industry experience with strategic leadership responsibility.
• Deep expertise in oncology and non-oncology drug development, including Phase 1 dose-escalation and registrational trial design for targeted small molecules.
• Experience translating in-vitro and in-vivo data into human PK and dose predictions, with knowledge of NONMEM, GastroPlus, or Simcyp.
• Experience selecting and managing global CROs and external vendors.
• Proven experience authoring IND and NDA clinical pharmacology sections and interacting with agencies including the FDA and EMA.

Nice to have

• Experience building translational pharmacology capabilities from the ground up.
• Strong interest in AI-first workflows, predictive human PK, DDI tools, and clinical data automation.

Culture & Benefits

• Hybrid working model with regular in-person collaboration.
• Interdisciplinary collaboration across Discovery, Clinical, Regulatory, drug discovery, and machine learning teams.
• Culture centered on thoughtful, brave, determined, and collaborative work.
• Commitment to equal employment opportunity and reasonable workplace accommodations.