Systems & Performance
we leadC++ development
Modern C++ (17 / 20) for performance-sensitive modules, embedded-adjacent tools, native SDKs, CMake / Conan build systems, and AI-inference engines (llama.cpp / ggml).
Sample projects we'd take
Python ML inference → llama.cpp / ggml port
$15k–$30k · 3 weeks
Port a Python ML inference path to llama.cpp / ggml C++ binaries. Bypass GIL overhead, reduce GPU dependence, ~60% cost / latency reduction on supported workloads.
C++ codebase refactor + CMake cleanup + Python binding
$10k–$25k · 2-4 weeks
Profile and refactor a C++ processing module. Modern C++17/20 idioms (smart pointers, move semantics, ranges). Clean up CMake/Conan. Expose a clean Python binding via pybind11.
Edge inference runtime on ARM64
$25k–$50k · 4-6 weeks
PyTorch model exported to TorchScript, executed via custom C++ allocator on ARM64. Quantization, op fusion, memory-mapped weights. Target: device-class latency budget.
Why C++ in 2026
Rust is eating new systems work, deservedly so. But C++ still owns the domains where physics, legacy, and compute intersect — game engines, quant trading, computer-vision pipelines on edge hardware, AI inference engines. The existing ecosystems (llama.cpp, ggml, PyTorch C++ runtime, Boost, Eigen, OpenCV) and the deterministic performance profile of modern C++ are unmatched. We write C++17/20 with smart pointers, move semantics, std::ranges, and std::expected so you don’t inherit the memory-safety nightmares of 1998-vintage code.
Honest caveats
C++ is the wrong call if you’re building a web backend, a REST API, or a 3-week MVP. The compile times alone will kill your iteration speed. If you don’t absolutely need deterministic memory management, direct hardware access, or AI-inference performance, you’re paying a massive developer-experience tax for no user-facing benefit. Use Go for concurrency, Rust for safe systems, Python for AI orchestration. We use C++ only when the hardware demands it.
When to pick this · when not to
When to pick
Deterministic latency, legacy C++ estate, native SDK integration, performance-sensitive AI inference.
When not to pick
Web backend, MVPs that need PMF validation in 3 weeks, or safety-critical firmware.
Different language?
If your project isn't a fit for C++, we'll recommend the right one. Send the brief — we'll come back inside 48 hours with our honest pick.