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Machine Learning Engineer

2 months ago

Cambridge, Cambridgeshire, United Kingdom CuspAI Full time
About CuspAI

CuspAI is a pioneering AI company dedicated to revolutionizing the field of materials science through cutting-edge machine learning technology.

Job Summary

We are seeking a highly skilled Machine Learning Engineer to join our world-class team of AI researchers and materials scientists. As a key member of our team, you will play a crucial role in developing and optimizing our machine learning-based software platform for materials discovery and optimization.

Key Responsibilities
  • Design, develop, train, and evaluate cutting-edge machine learning models for materials discovery and optimization.
  • Develop tools to enable large-scale machine learning experiments across distributed computing systems, maximizing the use of available resources.
  • Optimize model performance, scalability, and robustness for production use within our computational platform for materials analysis and prediction.
  • Create innovative tools for material property prediction and design in partnership with domain experts.
Requirements
  • Proven experience developing, training, and deploying large-scale machine learning models in distributed setups.
  • Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and orchestration tools like Kubernetes for large-scale machine learning model training and deployment.
  • Expert understanding of modern Python and working knowledge of at least one other programming language.
  • Familiarity with machine learning research and development.
  • At least 3 years of experience developing software in a team.
  • Bachelor's degree or higher in Computer Science, Materials Science, Physics, Chemistry, or a related technical field; equivalent practical experience considered.
  • Passionate about combating climate change and driven to make a significant impact.
  • Strong team player with excellent communication skills, thriving in collaborative and interdisciplinary environments.
Preferred Qualifications
  • Knowledge of materials science, computational chemistry, or climate-related technologies.
  • Strong knowledge of C++, CUDA, or other relevant languages.
  • Contribution to open-source projects with a scientific computing and/or machine learning focus.
  • Experience collaborating with research teams to prototype and productionize machine learning models for materials science or related fields.
  • Expertise in data structures and algorithms, especially those relevant to materials informatics.
  • PhD in Computer Science, Materials Science, Physics, Chemistry, or a related technical field; or equivalent practical experience.