Apheris
Director of ML Research – AI Applications(m/w/x)
Full-timeWith HomeofficeSenior
Berlin
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APApheris
Technical Lead - Structural Biology Networks(m/w/x)
Berlin
Full-timeWith Home OfficeSenior
AI/ML
Nejo AI Summary
Leading AI structural biology model programs, building federated co-folding models, and implementing ML applications in protein modeling. 5+ years applying ML to scientific/biological problems required. Early-stage virtual share options, wellbeing budget.
Requirements
- PhD, MSc, or equivalent experience in relevant field
- 5+ years applying ML to scientific/biological problems
- Experience in structural biology, protein modeling, co-folding, or binding prediction
- Hands-on experience with modern ML systems in Python and PyTorch
- Experience with large-scale models (OpenFold, AlphaFold, etc.)
- MLOps or ML infrastructure experience
- Kubernetes-based training, evaluation, or deployment workflows
- Ability to define success criteria and validate model quality
- Ensuring robust ML releases for real-world use
- Led delivery of complex ML projects
- Setting technical direction for ML projects
- Managing ML project risks and dependencies
- Driving teams toward high-quality ML releases
- Player-coach role: mentoring engineers and scientists
- Direct contribution to modeling, experimentation, or architecture
- Effective collaboration with stakeholders
- Turning ambiguous requirements into technical plans
- Experience with federated learning or privacy-preserving ML
- Experience with distributed or multi-party training environments
- Experience with Go or other systems programming languages
- Production-grade model delivery in regulated environments
- Experience in pharmaceutical, biotech, or high-trust environments
- Publication record in top-tier ML venues
- Publication record in computational/structural biology venues
Tasks
- Lead delivery of AI Structural Biology model programs
- Build and deliver federated co-folding models
- Stay hands-on in modeling, architecture, evaluation, and engineering
- Implement ML applications in structural biology
- Fine-tune and extend foundational models like OpenFold, Boltz-2, and ESMFold
- Ensure high-quality model releases meet milestones
- Translate ambiguous goals into clear plans and priorities
- Guide evaluation decisions and deliver results to stakeholders
- Surface risks, blockers, bugs, and technical trade-offs early
- Align consortium members on objectives and delivery expectations
- Work with product, engineering, research, and leadership
- Ensure application requirements shape the model roadmap
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- ML
- Python
- PyTorch
- OpenFold
- AlphaFold
- Boltz
- ESM
- MLOps
- Kubernetes
- Go
Benefits
Competitive Pay
- Industry-competitive compensation
- Early-stage virtual share options
Additional Allowances
- Wellbeing budget
- Work-from-home budget
- Co-working stipend
Mental Health Support
- Mental health support
Learning & Development
- Learning budget
More Vacation Days
- Generous holiday allowance
Other Benefits
- Office days at Berlin HQ or European location
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Apheris and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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APApheris
Technical Lead - Structural Biology Networks(m/w/x)
Berlin
Full-timeWith Home OfficeSenior
AI/ML
Nejo AI Summary
Leading AI structural biology model programs, building federated co-folding models, and implementing ML applications in protein modeling. 5+ years applying ML to scientific/biological problems required. Early-stage virtual share options, wellbeing budget.
Requirements
- PhD, MSc, or equivalent experience in relevant field
- 5+ years applying ML to scientific/biological problems
- Experience in structural biology, protein modeling, co-folding, or binding prediction
- Hands-on experience with modern ML systems in Python and PyTorch
- Experience with large-scale models (OpenFold, AlphaFold, etc.)
- MLOps or ML infrastructure experience
- Kubernetes-based training, evaluation, or deployment workflows
- Ability to define success criteria and validate model quality
- Ensuring robust ML releases for real-world use
- Led delivery of complex ML projects
- Setting technical direction for ML projects
- Managing ML project risks and dependencies
- Driving teams toward high-quality ML releases
- Player-coach role: mentoring engineers and scientists
- Direct contribution to modeling, experimentation, or architecture
- Effective collaboration with stakeholders
- Turning ambiguous requirements into technical plans
- Experience with federated learning or privacy-preserving ML
- Experience with distributed or multi-party training environments
- Experience with Go or other systems programming languages
- Production-grade model delivery in regulated environments
- Experience in pharmaceutical, biotech, or high-trust environments
- Publication record in top-tier ML venues
- Publication record in computational/structural biology venues
Tasks
- Lead delivery of AI Structural Biology model programs
- Build and deliver federated co-folding models
- Stay hands-on in modeling, architecture, evaluation, and engineering
- Implement ML applications in structural biology
- Fine-tune and extend foundational models like OpenFold, Boltz-2, and ESMFold
- Ensure high-quality model releases meet milestones
- Translate ambiguous goals into clear plans and priorities
- Guide evaluation decisions and deliver results to stakeholders
- Surface risks, blockers, bugs, and technical trade-offs early
- Align consortium members on objectives and delivery expectations
- Work with product, engineering, research, and leadership
- Ensure application requirements shape the model roadmap
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- ML
- Python
- PyTorch
- OpenFold
- AlphaFold
- Boltz
- ESM
- MLOps
- Kubernetes
- Go
Benefits
Competitive Pay
- Industry-competitive compensation
- Early-stage virtual share options
Additional Allowances
- Wellbeing budget
- Work-from-home budget
- Co-working stipend
Mental Health Support
- Mental health support
Learning & Development
- Learning budget
More Vacation Days
- Generous holiday allowance
Other Benefits
- Office days at Berlin HQ or European location
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Apheris and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Apheris
Industry
Pharmaceuticals
Description
Apheris builds AI applications for pharmaceutical R&D, enabling secure collaboration on large AI models to accelerate drug discovery.
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