Apheris
Director of ML Research – AI Applications(m/w/x)
Vollzeitmit HomeofficeSenior
Berlin
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APApheris
Technical Lead - Structural Biology Networks(m/w/x)
Berlin
Vollzeitmit HomeofficeSenior
AI/ML
Nejo KI-Zusammenfassung
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.
Anforderungen
- 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
Aufgaben
- 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
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- ML
- Python
- PyTorch
- OpenFold
- AlphaFold
- Boltz
- ESM
- MLOps
- Kubernetes
- Go
Benefits
Attraktive Vergütung
- Industry-competitive compensation
- Early-stage virtual share options
Sonstige Zulagen
- Wellbeing budget
- Work-from-home budget
- Co-working stipend
Mentale Gesundheitsförderung
- Mental health support
Weiterbildungsangebote
- Learning budget
Mehr Urlaubstage
- Generous holiday allowance
Sonstige Vorteile
- Office days at Berlin HQ or European location
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Apheris erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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Technical Lead - Structural Biology Networks(m/w/x)
Berlin
Vollzeitmit HomeofficeSenior
AI/ML
Nejo KI-Zusammenfassung
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.
Anforderungen
- 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
Aufgaben
- 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
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- ML
- Python
- PyTorch
- OpenFold
- AlphaFold
- Boltz
- ESM
- MLOps
- Kubernetes
- Go
Benefits
Attraktive Vergütung
- Industry-competitive compensation
- Early-stage virtual share options
Sonstige Zulagen
- Wellbeing budget
- Work-from-home budget
- Co-working stipend
Mentale Gesundheitsförderung
- Mental health support
Weiterbildungsangebote
- Learning budget
Mehr Urlaubstage
- Generous holiday allowance
Sonstige Vorteile
- Office days at Berlin HQ or European location
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Apheris erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Apheris
Branche
Pharmaceuticals
Beschreibung
Apheris builds AI applications for pharmaceutical R&D, enabling secure collaboration on large AI models to accelerate drug discovery.
Noch nicht perfekt?
- Apheris
Director of ML Research – AI Applications(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin - Apheris
Senior ML Researcher – Molecular Privacy(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin - PAIR Finance GmbH
Team Lead Data Science(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin - ZDF Sparks GmbH
Senior AI Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin - Apheris
.AI Program Manager – Drug Discovery Networks(m/w/x)
Vollzeitmit HomeofficeSeniorBerlin