Research Engineer, Code Metal

• The ideal candidate will have a strong background in machine learning, programming, and applied research
• Bachelor’s degree in Electrical Engineering, Computer Engineering, or a closely related field, or equivalent professional experience
• At least 1+ years in an applied research or development role focusing on machine learning and deep learning
• Strong understanding of machine learning techniques
• Proven track record of developing, scaling, and deploying machine learning models, particularly in a cloud or distributed computing environment
• Programming experience in Python and hands-on experience with frameworks such as PyTorch
• Familiarity with software engineering best practices, including version control (Git), code reviews, and continuous integration/deployment (CI/CD)
• If you are passionate about machine learning and applied research, and looking to make a significant impact, we would love to hear from you

Desirable

• We’re looking for passionate and experienced Research Engineers to become an integral part of our research team
• This is an incredible opportunity to join an experienced founding team who have collectively raised $1bn+ in capital across several previously successful ventures and lead AI Research within the business
• In this role, you will collaborate with a small team of talented researchers and engineers on exciting new projects in program synthesis and code transpilation, blending formal methods and modern deep learning architectures like graph neural networks and large language models
• Design methods, tools, and infrastructure to push forward the state of the art in program synthesis
• Define research goals informed by practical engineering concerns
• Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, GPU, and cloud training infrastructure)
• Work with a distributed team
• Contribute to publications and open-sourcing efforts