Senior Machine Learning Research Engineer

Symbolica is building a new foundation for large-scale AI using structured, interpretable reasoning. We are expanding our team and seeking machine learning research engineers to contribute to the development of our cutting-edge code synthesis and theorem proving models. This is an opportunity to be part of a transformative project and make significant contributions to the field of AI.

Responsibilities:Contribute to the design and implementation of machine learning architectures and algorithms for theorem proving, code synthesis, and text generationScale prototype models up using distributed training techniquesDevelop optimized GPU kernels to maximize model performanceIdentify performance bottlenecks using benchmarking and profiling toolsDesign and implement new mechanisms for model parallelismDesign and execute experiments to guide model development process while making effective use of compute budgetDevelop tools to gain insight into model behavior via fine-grained reporting and visualizationMaintain a deep understanding of current techniques in deep learning. Understand, implement, and improve on methods described in machine learning literatureCollaborate with a team of machine learning researchers and engineers to achieve project goals

Qualifications:Proficiency with Python deep learning libraries such as PyTorch and JAXExperience with distributed training of large scale deep learning modelsFive years of experience in non-academic machine learning engineering roles, or two years with a relevant PhDNice to have: Proficiency with GPU kernel development using CUDA or Triton

In-person in our Bay Area office is preferred, but we will be happy to consider exceptional candidates in other locations.

We offer competitive compensation, including equity, health insurance, and 401k benefits. Salary and equity levels are commensurate with experience and location.