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About CuspAI
CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry, and engineering.
We are tackling some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the beginning of what our search engine for next-generation materials will unlock.
We invite you to be part of a dynamic, innovative team at the intersection of AI and materials science, working to build impactful partnerships that drive innovation, scalability, and industry collaboration. This work is meaningful—your work will make a difference.
We’re on the cusp of the on-demand materials era. Join us.
The Role
As we grow, we are seeking a Data Engineer to play a crucial part in driving our research and development efforts forward.
Your Impact
As a Data Engineer, you will be part of the new team building the foundational infrastructure that bridges raw chemical data and machine learning models. Your focus will be on:
- Building pipeline infrastructure and tooling for data ingestion.
- Transitioning towards self-serve setups for scientific team members.
- Securing, collecting, cleaning, standardising, and tagging chemical datasets.
- Ensuring high-quality training data for ML researchers while collaborating with the chemistry team to maintain scientific accuracy.
Responsibilities
Data Pipeline Development
- Design and build robust data pipelines for:
- Materials science datasets
- Experimental results
- Computational chemistry outputs
- Integrate diverse data sources:
- Materials databases
- Literature and patent filings
- Laboratory instruments
- Develop automated workflows for processing:
- Crystallographic data
- Molecular structures
- Materials properties (No prior domain expertise required—we’ll support your learning!)
- Construct scalable systems to support:
- High-throughput computational chemistry calculations
- Experimental data
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Data Quality & Standardisation
- Collaborate with research teams to implement:
- Automated quality checks for:
- Crystal structure data
- Chemical compositions
- Experimental measurements
- Automated quality checks for:
- Establish standardisation protocols for:
- Materials nomenclature
- Units and conditions
- Build monitoring systems to maintain data integrity across pipelines
Collaboration & Integration
- Partner with:
- ML researchers to define data requirements for model training and inference
- Materials scientists to embed domain knowledge in data schemas
- Laboratory automation systems and computational chemistry software
- Support real-time data needs for AI-driven materials discovery experiments
Requirements
Must-Have Skills & Qualifications
- A passion for enabling scientists to address global challenges through emerging materials technology. -Proficiency as a tool and infrastructure builder, with experience creating reliable, scalable data pipelines for self-serve use. -Minimum 3+ years of experience in data engineering (preferably in scientific research environments). -Acts as subject matter expert in data engineering practices and can deliver autonomously while advising best practices. -Strong Python and database skills, with experience in large-scale data processing. -Experience with workflow orchestration (Airflow, Prefect, Dagster, or similar). -Command of containerisation (Docker, Kubernetes) and CI/CD practices. -Confident handling complex or large datasets, especially in scientific domains. -Fast learner in new tools/systems, with an aptitude for building infrastructure at scale. -Comfortable applying DevOps principles.
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Bonus Points (Appliance)
-Work experience in scientific computing (simulations/experiments). -Familiarity with machine learning data pipelines and MLOps, including pre/post-processing. -Academic background in Materials Science, Chemistry, Chemical Engineering, or related fields. -Understanding of crystallography, materials properties, and computational chemistry.
Benefits
- Competitive salary—valuing both performance and long-term growth
- Equity in CuspAI—gaining a stake in our company’s success
- Generous time off: 28 days holiday (DE, NL, UK) or 21 days (JP, SG, US), plus all applicable local holidays
- parantalaave: 26 weeks paid leave for primary caregivers and 12 weeks for secondary caregivers
- Professional development budget to support continuous learning
- The chance to solve meaningful problems—accelerate breakthroughs in sustainability and climate technology through cutting-edge AI solutions
- Work in a collaborative, interdisciplinary environment, blending leading AI research, computational chemistry, and experiments
- Contribute alongside world-class researchers and engineers known for mentorship and knowledge-sharing
Culture & Philosophy
Join us in reshaping the future of materials with AI. Together, we can deliver industry-changing solutions for a more sustainable world.
CuspAI is an equal-opportunities employer, committed to fostering a diverse and inclusive workplace. We strive for equity across gender, race, disability, age, and sexual orientation, among other areas. We actively encourage applications from all backgrounds, as diversity fuels creativity and innovation.
If you require accommodations during or after the interview process, please let us know—reasonable adjustments are prioritized.
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