Head of AI Research

Meyandy LLC; Berlin; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Meyandy LLC, a seed-stage deeptech company in Berlin, is seeking a senior ML researcher to define and lead AI-native materials discovery. You will shape the research roadmap, build cross-functional collaborations, and drive the Materials World Model across experiments and simulations.

Candidates should have a PhD and 7+ years in AI/ML research, with a strong track record in representation learning or foundation models and the ability to translate theory into lab-ready workflows.

Qualifikationen

• Advanced degree (PhD strongly preferred) in machine learning, computational physics, chemistry, materials science, or a closely related field.
• 7+ years of AI/ML research experience with leadership of senior individual contributors.
• Deep expertise in representation learning, scientific ML, or foundation models with relevance to physical or chemical systems.
• Strong intuition for physics, chemistry, or materials science and their governing constraints.
• Proven ability to operate at the boundary between theory, systems, and real-world experimental feedback.
• Demonstrated scientific judgment and ability to communicate complex ideas clearly to diverse audiences.
• English fluency required; additional languages are a plus.

Aufgaben

• Define a clear research vision and roadmap for AI-native materials discovery, setting thesis-level bets and identifying high-impact research directions.
• Identify where existing ML paradigms fall short for physical matter and specify what must be built from the ground up.
• Lead development of a Materials World Model that integrates experiments, simulations, and learned representations across scales.
• Collaborate cross-functionally with Programs, Hardware & Automation, and Software Architecture teams to embed research into end-to-end discovery loops.
• Ensure all models and pipelines are grounded in physical reality and validated against experimental feedback.
• Balance long-horizon research ambitions with near-term deliverables and scientific rigor.
• Build, hire, mentor, and challenge a world-class team of senior ML researchers and computational scientists.
• Foster a culture of deep thinking, honest evaluation, scientific taste, and intellectual courage.
• Influence the broader field through external collaborations, publications, and a clear view on the future of scientific AI.

Kenntnisse

AI/ML research leadership

Representation learning

Scientific ML

Foundation models

Physics/chemistry background

Cross-functional collaboration

Communication to diverse audiences

Ausbildung

PhD in ML or related field

Jobbeschreibung

About the Role

We are a seed-stage deeptech company building an advanced materials acceleration platform at the intersection of physics-informed AI, robotics, and autonomous experimentation — with a focus on the energy sector and beyond. Our mission: compress decades of materials discovery into years by connecting frontier machine learning with real-world experimental pipelines.

What You’ll Do

• Define a clear research vision and roadmap for AI-native materials discovery, setting thesis-level bets and identifying high-impact research directions.
• Identify where existing ML paradigms fall short for physical matter and specify what must be built from the ground up.
• Lead development of a Materials World Model that integrates experiments, simulations, and learned representations across scales.
• Collaborate cross-functionally with Programs, Hardware & Automation, and Software Architecture teams to embed research into end-to-end discovery loops.
• Ensure all models and pipelines are grounded in physical reality and continuously validated against experimental feedback — not just data-driven patterns.
• Balance long-horizon research ambitions with near-term deliverables and scientific rigor.
• Build, hire, mentor, and challenge a world-class team of senior ML researchers and computational scientists.
• Foster a culture of deep thinking, honest evaluation, scientific taste, and intellectual courage.
• Influence the broader field through external collaborations, publications, and a clear, opinionated point of view on the future of scientific AI.

What We’re Looking For

• Advanced degree (PhD strongly preferred) in machine learning, computational physics, chemistry, materials science, or a closely related field.
• 7+ years of experience in AI/ML research, including demonstrated leadership of senior individual contributors.
• Deep expertise in representation learning, scientific ML, or foundation models with relevance to physical or chemical systems.
• Strong intuition for — or direct background in — physics, chemistry, or materials science and their governing constraints.
• Proven ability to operate at the boundary between theory, systems, and real-world experimental feedback.
• Demonstrated scientific judgment: comfort with irreversible prioritization calls under uncertainty, and the ability to communicate complex ideas clearly to diverse audiences.
• English fluency required; additional languages are a plus.
• Based in Berlin, Germany or willing to relocate.

Nice to Have

• Experience working in or alongside autonomous laboratory / high-throughput experimentation environments.
• Background at national labs, research institutes, or research-forward industry settings (e.g., materials, energy, or chemical sectors).
• Track record of cross-disciplinary collaboration bridging ML and physical sciences.

Location & Work Arrangement

This is a full-time, on-site role based in Berlin, Germany. Candidates must be based in Berlin or willing to relocate. Visa sponsorship is not available for this position.

Why This Role

Rare opportunity to define an entire research discipline at an early-stage company with a technically ambitious mission. Work at the frontier of AI and physical science — where models must meet reality. Join a team with deep roots in top-tier research, national laboratories, and leading industrial science organizations. Shape the team, culture, and scientific direction from the ground up.