This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

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
• Long-session stability

You will define and evolve the core abstractions that inference features depend on, enabling new capabilities to be added without sacrificing performance or maintainability. This role is 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

Qualifications

• Excellent programming skills in C++, experience in Javascript is a bonus
• Strong experience with Llama.cpp and ggml inference engines, facilitating 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

Important information for candidates

Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:

• Apply only through our official channels.
• We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/
• Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles.
• Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS.
• Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io.
• We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.