Senior Machine Learning Scientist

The Opportunity:

Lead machine learning research projects to build world-class code synthesis algorithms using our powerful new structured cognition technology

Our Company:

Symbolica is building a new foundation for large-scale AI using structured, interpretable reasoning. We are expanding our team and seeking machine learning scientists 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.

The Role:

This is a full-time role located in San Carlos, CA, with flexibility for some remote work. As a Senior Machine Learning Scientist at Symbolica AI, you will be responsible for developing and implementing state-of-the-art foundation models for structured reasoning. You will work with deep learning models that manipulate structured data, learn algebraic structure, and ensure interpretability and verifiability.

Your Responsibilities

• Own a research project within the broader Symbolica agenda, and deliver high quality results on project timelines
• Contribute to the design and implementation of machine learning architectures and algorithms for theorem proving, code synthesis, and text generation
• Train and evaluate models and optimize hyperparameters while making effective use of compute budget
• Maintain a deep understanding of current techniques in deep learning. Understand, implement, and improve on methods described in machine learning literature, without relying on published code
• Translate business objectives into technical requirements and communicate technical progress and obstacles to non-technical stakeholders
• Collaborate with a team of machine learning researchers and engineers to achieve project goals

Qualifications:

• Demonstrated ability to perform all responsibilities
• PhD in mathematics, statistics, computer science, or a related field
• 2 years work experience in machine learning
• Proficiency with Python deep learning libraries such as PyTorch
• Research published in NeurIPS, ICML, ICLR, AAAI, COLT, etc.
• Specific previous experience with one or more of following: diffusion models, large language models, knowledge graph generation and traversal, automated theorem proving, compiler design, code synthesis
• Excellent communication and collaboration abilities

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.