Postúlate en Kit Empleo: kitempleo.com.ar/empleo/q0abk

About the role:

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.

About the job

You’ll lead a cross‑functional pod that spans the full stack, from C++ inference engines to JavaScript applications. Your responsibility is to ensure that local AI capabilities ship reliably and perform well across devices. You’ll balance hands‑on technical work with team coordination, guiding foundation and middleware engineers toward shared goals. This role is idóneo for someone who understands both the low‑level challenges of edge AI and the product‑facing needs of app developers, and wants to drive the delivery of cohesive, production‑ready local AI systems.

Responsibilities

- 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
- Manage a cross‑functional team (pod) made of middleware (JS), foundation (C++), QA and documentation engineers to produce high quality deliverables
- Regularly assess, both qualitatively and quantitatively, our position in the market with regards to similar products or platforms
- Leverage the expertise of technical architects to ensure robust architectural choices and code quality
- Ensure stable releases by following precise internal release processes

Qualifications

- Excellent programming skills in C++
- Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures
- Good understanding of deep learning concepts and model architectures
- Experience with transformers, LLMs, diffusion models
- Demonstrated ability to rapidly assimilate new technologies and techniques
- Experience managing a small, specialized, cross‑functional team (pod) of 3‑5 people
- Has a genuine passion for building good products that improve people's lives
- A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D;

Bonus points if

- You have extensive experience with JavaScript/TypeScript
- You understand the difficulties, nuances and importance of p2p technology
- You have experience with any of Vulkan, Metal and OpenCL
- You have productionized models

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Postúlate en Kit Empleo: kitempleo.com.ar/empleo/q0abk

📌 Lead AI Inference Engineer QVAC 100% remote Worldwide (Argentina)
🏢 Framework Ventures
📍 Argentina