Requirements: English
Company: CuspAI
Region: Amsterdam , North Holland
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.
Were on the cusp of the on-demand materials era. Join us.
As we grow, we are seeking a Machine Learning Engineer with an operations focused background to play a crucial part in developing our cutting-edge ML-based software platform.
Join Our Mission:
We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration.
Impact:
In this role, you will develop our cutting-edge ML-based software platform aimed at transforming materials science to address critical climate challenges. You will work closely with our AI researchers, materials scientists, and engineers to build and optimise our core platform.
Working in a highly creative and iterative environment, you will collaborate with leading experts across multiple disciplines to turn groundbreaking research into practical, scalable software solutions. We believe that close collaboration, creativity, and spontaneity within a team are essential to achieving extraordinary results. Therefore, this position is primarily on-site. We also believe that truly exceptional work thrives in a culture built on trust, empathy, kindness, open-mindedness, and curiosity.
As this is a newly created team and position, you will have the chance to shape your role and make a significant impact on our platform''s development. Your experience in software engineering for machine learning applications will be essential in bridging the gap between cutting-edge AI research and real-world implementation in materials science.
What You Will Do:
- Build Advanced ML Solutions: Be part of a world-class ML Research, Materials and Data Engineering team to design, develop, train, and evaluate cutting-edge ML models for materials discovery and optimisation.
- Architect Cloud-Based ML Platform: Build a scalable ML platform in the cloud to allow for rapid experimentation and prototyping, aligned with our computational chemistry platform.
- Enable Distributed Computing: Develop tools to enable large-scale ML experiments across distributed computing systems.
- Optimise Production Performance: Enhance model performance, scalability, and robustness for production use within our computational platform for materials analysis and prediction.
Skills and Qualifications:
- Essential:
- Educational Background: Bachelor''s degree or higher in Computer Science, Materials Science, Physics, Chemistry, or a related technical field; equivalent practical experience considered.
- ML Workflow Expertise: Hands-on experience designing, managing and deploying complex ML workflows on Kubernetes to support our research effort.
- Framework Proficiency: Proficiency with frameworks like JAX, TensorFlow, or PyTorch.
- Programming Skills: Proficiency in Python is preferred, Rust and Golang are desirable alternatives.
- Cloud Computing: Advanced experience with cloud computing platforms (AWS, GCP, Azure), GPUs and storage technologies.
- DevOps Excellence: Strong experience in DevOps best practices, Configuration as Code, Terraform, Helm, Kapitan or similar technologies.
- Infrastructure Passion: Enthusiastic about building scalable and reliable infrastructure systems for research.
- Large-Scale ML Experience: Experience developing, training and deploying large-scale ML models in distributed setups.
- RD Workflow Scaling: Experience setting up and scaling machine learning workflows, especially in RD focused environments.
- Performance Optimisation: Understanding how to speed and scale up machine learning models from the perspective of infrastructure, hardware, cost and performance.
- Mission-Driven: Passionate about combating climate change and driven to make a significant impact.
- Collaborative Mindset: Strong team player with excellent communication skills, thriving in collaborative and interdisciplinary environments.
- Bonus:
- Scientific Interest: Keen interest and/or experience in natural science research.
- ML Method Knowledge: Familiarity with modern machine learning methods.
- Scientific Computing: Familiarity with traditional scientific computing setups.
Additional Considerations
This role is based in our Cambridge, Amsterdam or Berlin office, with the expectation of being present on-site for three days per week. Some travel will be required t