This job posting has expired
Expired on March 30, 2026
Lead AI Inference Engineer
Job Description
At Tether, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. 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 ideal 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
- Managing a cross functional team (pod) made of middleware (JS), foundation (C++), QA and documentation engineers to produce high quality deliverables
- Regularly assessing, both qualitatively and quantitatively, our position in the market with regards to similar products or platforms
- Leveraging the expertise of technical architects to ensure robust architectural choices and code quality
- Ensuring stable releases by following precise internal release processes
Qualifications
- Excellent programming skills C++
- Strong experience with Llama.cpp and ggml inference engines
- Good understanding of deep learning concepts and model architectures
- Experience with transformers and LLMs
- Has experience managing a small, specialized, cross functional team (pod) of 3-5 people
- A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D