➡️ Apply here: Senior AI Inference Engineer
👩💼 Want to stand out? Improve your resume to appeal to recruiters, hiring managers, and Applicant Tracking Systems. ➡️ Improve your resume
Join Tether and Shape the Future of Digital FinanceAt Tether, we’re not just building products…See this and similar jobs on LinkedIn.
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.
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
Excellent programming skills in C++, experience in Javascript is a bonus
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
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 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