Join Our Team

Help us shape the future of materials science and molecular innovation

Open Positions

Build and optimize production systems for AI/ML training and inference pipelines that handle multimodal scientific data.

Experience with ML operations (MLOps) and production AI systems
Familiarity with frameworks like PyTorch, TensorFlow, or JAX
Background in distributed computing and/or high-performance scientific computing
Knowledge of containerization and orchestration tools (Docker, Kubernetes)

Architect and design AI models specifically aimed at scientific discovery in materials science.

Background in deep learning research, particularly with generative models
Interest in applying AI to scientific domains, preferably chemistry or materials science
Understanding of multimodal learning approaches combining text, structural data, and experimental results
Programming proficiency in Python and relevant ML frameworks

Develop systems that integrate diverse scientific data sources into cohesive AI training and inference pipelines.

Experience with multimodal deep learning architectures and fusion techniques
Interest in natural language processing for scientific literature analysis
Background in processing structured scientific data (molecular structures, experimental measurements)
Software engineering skills with experience in ML systems