fundamental - Applied AI Engineer
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Requirements
• Strong software engineering fundamentals with expert-level Python and C++ • Hands-on experience bridging Python and C++ (PyBind11, Cython, or custom extensions) • Experience developing and maintaining ML models in production • Strong understanding of neural networks • Track record of optimizing performance-critical code • Strong profiling and debugging skills (CPU, memory, latency) • Experience with tabular ML approaches (transformers, tree/NN hybrids, learned embeddings) • Familiarity with PyTorch internals or writing custom ops • Experience optimizing training loops, data pipelines, or inference engines • Background in numerical computing or systems programming • Exposure to large-scale ML infrastructure (distributed training, batching, caching)
Responsibilities
• Take part in development and optimization of a large neural network-based tabular model implemented in Python. • Profile training and inference pipelines to identify performance bottlenecks. • Rewrite critical components in C++ where necessary using PyBind11 or custom extensions. • Improve memory efficiency, latency, and throughput across the entirety of our ML systems handling tabular data. • Ensure correctness, numerical stability, and reproducibility as new capabilities are developed and productionized. • Collaborate with machine learning researchers on bringing new features into production use cases. • Maintain clean abstractions, comprehensive tests, and clear documentation for the systems being worked on. • Shape architectural decisions regarding our ML systems that handle tabular data inputs.
Benefits
• Competitive compensation with salary and equity options. • Comprehensive health coverage including medical, dental, vision insurance as well as a 401K plan. • Fertility support services along with paid parental leave for all new parents (adoptive or surrogate). • Relocation assistance for employees relocating to one of our office locations.
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