AI Program Manager – Drug Discovery Networks
TLDR
Drive execution and growth of federated networks, ensuring structured progress and measurable impact in drug discovery initiatives with top pharmaceutical partners.
About Apheris
At Apheris, we are building the future of how AI is applied in pharmaceutical R&D.We enable leading pharmaceutical teams to discover and develop drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability.
Across these networks, models are trained on proprietary industry datasets to achieve higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that enable teams to run them at scale, further customize them, and integrate them into existing R&D workflows.
Examples of our live networks include:
- AI Structural Biology (AISB) Network: Top 20 pharma companies collaborate in the field of co-folding, structure-based binding affinity predictions and antibody design.
- ADMET Network: Top 50 pharma companies and biotechs collaborate to improve small-molecule property prediction and expand to further drug modalities.
- Antibody Developability Network: Pharma partners collaborate to federate historical and purpose-built antibody developability datasets for secure ML training, without data leaving each partner’s environment.
About the role
We are hiring AI Program Managers to drive execution and growth across one or more of Apheris’ federated networks, including scaling existing networks and/or helping build new ones from the ground up.This is a high-ownership, customer-facing role. You will drive structured progress across complex, multi-party initiatives and ensure that partners, internal teams, and workstreams move in lockstep. Beyond execution, you will actively shape how networks evolve: how they scale, how partners engage, and how value is created over time.
A central part of the role is translating network goals into concrete execution. You will drive program progress across customers, prepare materials for scientific and commercial discussions, shape follow-ups, and convert roadmap priorities into clear workstreams. You will work closely with business development, ML scientists, and product and engineering teams to maintain momentum.
You will also drive adoption of federated models within partner organizations and embed them into active drug discovery programs. This includes strategic account management, increasing application usage, and ensuring outputs deliver measurable impact in real workflows. You will coordinate across internal and external teams, aligning priorities, resolving dependencies, and driving execution end-to-end.
What you will do
Build new federated networks- Scope new network opportunities based on market demand and partner needs
- Validate concepts with prospective partners through structured discussions and early design collaboration
- Play an active role in business development by identifying potential partners, having introductory conversations, and securing commitments
- Set up new networks, including defining initial scope, timelines, and partner contributions
- Own execution across one or more Apheris networks, working directly with leading pharma partners to turn their data into shared, high-performance models
- Drive federated network management end-to-end, from partner data onboarding and harmonization to model aggregation and delivery of weights and inference containers in collaboration with Apheris’ technical and domain experts
- Maintain and push forward a clear execution plan across partners, spanning data readiness, training runs, and benchmarking milestones
- Define how Apheris networks evolve, including adding new endpoints, expanding to new modalities, and increasing the value delivered to partners over time
- Work with BD and product to launch new network tracks and bring additional pharma partners into the network
- Turn emerging opportunities into scoped initiatives, proposals, and execution plans
- Act as the day-to-day counterpart to partner teams, working closely with senior scientists and leaders at top pharma companies
- Lead working sessions on model performance, benchmarking results, and deployment approaches together with Apheris’ domain experts, shaping how federated models are used in practice
- Drive discussions toward clear decisions, whether on evaluation criteria, rollout strategies, or next areas of investment
- Build trusted relationships with partners while pushing conversations forward and maintaining a high bar for progress
- Identify where to push, expand scope, or activate additional stakeholders
- Bring federated models into real-world usage by driving deployment into partner environments and integration into existing workflows
- Help partners move from evaluating models to using them in active drug discovery programs
- Track how models are used across the network and identify opportunities to expand impact across teams and programs
- Continuously improve how Apheris models are delivered and consumed in collaboration with Product, making it faster and easier for partners to realize value
What we expect from you
- 5+ years of experience in scientific or technical program management, top-tier consulting, partnerships, product-adjacent execution, or similar roles in complex enterprise or multi-stakeholder environments
- Exceptional learning velocity, enabling you to quickly master unfamiliar domains and proactively close gaps in domain-specific knowledge (e.g., large molecules, ADMET, or related technical areas) with speed and accuracy
- Experience working with senior scientific stakeholders from the pharmaceutical and biotech industry
- Strong product mindset, with willingness to engage deeply with Apheris’ products and translate this into better partner outcomes and internal prioritization
- Proven ability to build new initiatives from the ground up and run and scale ongoing programs
- Exceptionally high degree of ownership, speed, and reliability
- Exceptional written and verbal communication skills in English (German is optional, as we interact internally and with all partners in English)
- Strong judgment on prioritization, blockers, and escalation
Nice to have
- Strong working knowledge of molecular machine learning and drug discovery workflows, with the ability to actively contribute to scientific discussions and challenge assumptions
- In-depth scientific expertise in molecular machine learning or drug discovery workflows
- Experience operating in consortium, network, or multi-party settings, including navigating competing incentives and managing cross-organization governance
- Experience supporting technical product rollouts or customer integrations
- Experience working with senior scientific stakeholders in biotech or pharma environments
What we offer you
- Industry-competitive compensation, including early-stage virtual share options
- Remote-first working – work where you work best
- Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget
- Generous holiday allowance
- Office Days at our Berlin HQ or a different European location (3x per year)
- A high-caliber, execution-focused team with experience from leading organizations
Benefits
Home Office Stipend
Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget
Office Days in Berlin or another European location
Office Days at our Berlin HQ or a different European location (3x per year)
Paid Time Off
Generous holiday allowance
Remote-Friendly
Remote-first working – work where you work best
Apheris builds a federated data network that enables life sciences organizations to securely collaborate on AI model training without sharing proprietary data. Our technology addresses the challenges of data silos in pharmaceutical R&D, allowing teams to enhance drug discovery processes and predict complex macromolecule structures faster.
- Founded
- Founded 2019
- Employees
- 11-50 employees
- Industry
- IT Services
- Total raised
- $12M raised