About the role
Fundamental is hiring an Applied AI Engineer to develop and optimize NEXUS, its large neural-network model for structured business data. The role focuses on Python model pipelines, profiling training and inference, and improving memory use, latency, throughput, correctness, and reproducibility. You will work with ML researchers to productionize new capabilities and help shape the architecture of tabular ML systems.
The position calls for expert-level Python and Rust, experience bridging the two languages, production ML model experience, and a record of optimizing performance-critical code. C++ integration, PyTorch internals, tabular ML methods, and large-scale ML infrastructure are useful additional experience. Fundamental offers salary and equity, health coverage, parental leave, and relocation support for moves to its offices.
Highlights
- Build and optimize a large neural-network tabular model.
- Improve ML training and inference performance using Rust and Python.
- Shape architecture for systems handling tabular data.
- Salary and equity, health coverage, and parental leave.
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