• You will own the inference backbone behind QVAC's local AI stack: the C++ systems layer that makes models run fast reliably and predictably on real user hardware • The role is centered on engineering quality at runtime level including startup behavior memory pressure throughput/latency balance and long-session stability • You will define and evolve the core abstractions that inference features depend on so new capabilities can be added without sacrificing performance or maintainability • Your work directly enables private on-device AI experiences and helps set the technical foundation for QVAC's next generation of peer-to-peer AI products • Work on deploying machine learning models to edge devices using the frameworks: llama.cpp ggml onnx • Collaborate closely with researchers to assist in coding training and transitioning models from research to production environments • Integrate AI features into existing products enriching them with the latest advancements in machine learning

• Own the inference backbone behind QVAC's local AI stack • Work on deploying machine learning models to edge devices • Collaborate closely with researchers to assist in coding and training models • Integrate AI features into existing products

• You will own the inference backbone behind QVAC's local AI stack: the C++ systems layer that makes models run fast, reliably, and predictably on real user hardware. • The role is centered on engineering quality at runtime level, including startup behavior, memory pressure, throughput/latency balance, and long-session stability. • You will define and evolve the core abstractions that inference features depend on, so new capabilities can be added without sacrificing performance or maintainability. • This is a role for someone who enjoys low-level problem solving, clear technical ownership, and building infrastructure that other teams trust in production. • Your work directly enables private, on-device AI experiences and helps set the technical foundation for QVAC's next generation of peer-to-peer AI products. • Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml, onnx • Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments • Integrate AI features into existing products, enriching them with the latest advancements in machine learning

• Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml, onnx • Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments • Integrate AI features into existing products, enriching them with the latest advancements in machine learning