Research Leader / Senior Scientist (Computational Drug Design)

Location: Cambridge, Massachusetts, United States. Hybrid work with office attendance required 3 days per week, currently Tuesday, Wednesday, and one additional team-dependent day.

Company

hirify.global applies frontier AI and machine learning to computational biology and drug discovery, building predictive and generative models to design novel medicines.

What you will do

• Lead drug design programs as a Program Lead or Computational Chemistry Lead, guiding projects from initiation toward clinical candidate selection.
• Apply AI-first approaches and provide technical and strategic direction for portfolio drug discovery programs.
• Collaborate with machine learning, biology, chemistry, platform, and external CRO teams to deliver scientific solutions.
• Define principles for integrating AI/ML into computational chemistry workflows and provide direction to ML platform teams.
• For Program Leadership roles, oversee CRO collaborations, prepare scientific proposals and reports, and lead programs through go/no-go milestones.
• Where applicable, line-manage and mentor teams of 2–3 computational chemists.

Requirements

• PhD in Computational Chemistry or a related scientific field, or equivalent industrial experience.
• 5+ or 8+ years of professional experience in computational drug design within a biotech, pharmaceutical, or CRO environment.
• Demonstrated project leadership and contributions to drug discovery programs, ideally from hit identification through lead optimisation or candidate nomination.
• Experience writing and implementing Python scripts and/or using pipelining tools for cheminformatics and molecular design workflows.
• Strong scientific record demonstrated through publications, patents, or presentations, with excellent communication and cross-functional collaboration skills.
• For people or program management roles, experience leading, mentoring, and developing high-performing scientific teams.

Nice to have

• Experience applying machine learning and generative AI to hit finding, virtual screening, active learning, molecular design, or lead optimisation.
• Knowledge of fragment-based drug design, PROTACs, molecular glues, PPI inhibitors, stabilisers, peptides, or other alternative modalities.
• Understanding of ADME and DMPK principles.
• Experience authoring scientific manuscripts, inventing composition-of-matter patents, or managing CRO activities.

Culture & Benefits

• Interdisciplinary collaboration across computational chemistry, machine learning, biology, and drug discovery.
• Supportive environment focused on inclusion, scientific growth, continuous learning, and professional development.
• Culture guided by curiosity, creativity, initiative, integrity, determination, and collaboration.
• Equal employment opportunity and accommodation support for candidates with disabilities or additional needs.