[Hiring] Lead Scientist @Apheris

Role Description

We're looking for a large molecule specialist to bring deep domain knowledge in antibody engineering, structural biology, and biologics to our networks. You'll help define the scientific workflows and modeling strategy for antibody-antigen co-folding, binder prediction, and developability prediction - working closely with our ML and engineering team, who own the actual model-building.

We need this person to give large molecules a real point of ownership at Apheris:

• Decide what's scientifically relevant as the network grows.
• Partner with stakeholders to speak with genuine drug-discovery credibility, not just AI credibility.

You don't need to write training code or build the models yourself. You do need enough AI/ML fluency to have a real, informed say in what gets built:

• Sanity-checking results.
• Catching where a modeling approach doesn't reflect biological reality.
• Helping translate scientific questions into a workable plan.

Qualifications

• PhD, MSc, or equivalent experience.
• 5+ years in structural biology, antibody engineering, immunology, protein engineering, or a related biologics discipline.
• Real hands-on experience in antibody design, developability, or binder discovery.
• Some exposure to applying AI/ML to biological problems.
• Comfortable partnering closely with ML/engineering teams.
• Clear communication across scientific and technical audiences, and with pharma partner stakeholders.

Requirements

• Define the scientific workflow, evaluation strategy, and benchmarking approach for large molecule programs.
• Use our product as a hands-on user and define user requirements for large molecule workflows.
• Drive adoption of large molecule models with pharma partners.
• Translate scientific and biological requirements from pharma partners into concrete inputs for the ML/engineering team.
• Review model outputs and evaluation results against real structural biology / antibody engineering knowledge.
• Represent Apheris's scientific perspective in partner conversations.
• Stay current on the large molecule AI/ML landscape.
• Work with product, ML, and engineering to ensure scientific requirements shape the roadmap.

Nice to have

• Familiarity with OpenFold, AlphaFold, Boltz, or similar structure prediction tools.
• Experience with antibody developability assays, immunogenicity, or biologics manufacturability.
• Direct experience with pharma partners or in a consortium/collaborative research setting.
• Publication record in structural biology, immunology, or antibody engineering venues.

Benefits

• Competitive compensation with early-stage virtual share options.
• Remote-first, with flexibility on work location.
• Wellbeing support: mental health resources, work-from-home budget, co-working stipend, learning budget.
• Generous holiday allowance.
• Optional office days at Berlin HQ or another European location (roughly 3x a year).
• An execution-focused team with backgrounds from leading organisations.