Applied AI Engineer
Fundamental4 months ago
Remote, EMEASenior
Responsibilities
- Develop and optimize a large neural network-based tabular model in Python.
- Profile training and inference pipelines to identify performance bottlenecks.
- Rewrite critical Python-limited components in Rust using PyO3 or custom extensions, with C++ as a secondary option.
- Improve memory efficiency, latency, and throughput across model pipelines.
- Ensure model correctness, numerical stability, and reproducibility.
- Collaborate with ML researchers to productionize new capabilities.
- Maintain clean abstractions, comprehensive tests, and clear documentation.
- Shape architectural decisions for ML systems handling tabular data.
Requirements
- Expert-level Python and Rust skills with strong software engineering fundamentals.
- Hands-on experience bridging Python and Rust using PyO3, maturin, or custom extensions.
- Experience developing and maintaining ML models in production.
- Strong understanding of neural networks.
- A track record of optimizing performance-critical code.
- Strong CPU, memory, and latency profiling and debugging skills.
- Preferred experience includes tabular ML, C++, Python-C++ bridging, PyTorch internals, custom operations, training or inference optimization, numerical computing, systems programming, large-scale ML infrastructure, Rust async programming, and SIMD or parallelism crates.
Benefits
- Competitive compensation including salary and equity.
- Comprehensive health coverage for employees and dependents.
- Paid parental leave for all new parents, including adoptive and surrogate journeys.
- Relocation support for employees moving to an office location.
- Mission-driven, low-ego culture valuing diversity of thought, ownership, and bias toward action.