AI Inference Engineer QVAC (100% remote Worldwide)
Role Overview
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 work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack.
This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure.
Key Skills for This Role
Full Job Posting
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 work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack.
This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure.
Responsibilities
- Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml
- 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
- Strong programming skills in C++
- Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures
- Experience with any GPU framework between Cuda, Vulkan, Metal, OpenCL
- 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 RD
- Bonus points if:
- You know how to train/fine-tune a LLM
- You have productionized models
- You have research experience in new model architectures
- You have experience with distributed systems
- Javascript experience
- 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. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.
- Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.
- 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.
- When in doubt, feel free to reach out through our official website.
About Tether
Cryptocurrency company behind the USDT stablecoin, providing blockchain infrastructure and digital asset technology for the global financial ecosystem.
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