About Symbolica
Symbolica is an AI research lab focused on advancing machine reasoning through category theory. The company blends cutting-edge theory with fast, practical engineering.
Role Overview – Founding GPU & Compiler Software Engineer
As an early engineer at Symbolica, you’ll focus on building and optimizing GPU kernels and algorithms to train and run symbolic reasoning models. You’ll work with tools like CUDA and CUTLASS, applying advanced compiler techniques to maximize performance on complex computations.
What You’ll Do
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Develop and tune high-performance GPU code for symbolic AI models.
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Apply compiler optimization strategies to enhance training and inference speeds.
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Combine theoretical rigor with fast execution in a research-driven environment.
About the Company
Founded in 2022, Symbolica has secured over $30 million in funding from top Silicon Valley investors.
What We’re Looking For
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Strong skills in a high-performance language like C, C++, Rust, Haskell, or Julia, plus working knowledge of Python.
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Solid experience with CUDA programming, including kernel design, compiler tuning, and performance optimization.
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Deep understanding of GPU internals: memory layout, scheduling, threading, etc.
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Background in compiler development or DSL optimization (e.g., LLVM, MLIR).
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Knowledge of tensor math and numerical algorithms.
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Bonus points for familiarity with LSP, linear algebra, or symbolic computation.
Benefits
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Competitive salary
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Significant equity ownership