• Monitor, analyse and communicate changes in global regulatory policies, and advise executive leadership on potential regulatory risks and opportunities, while driving initiatives to influence regulatory frameworks as well as monitoring for change across regulations to ensure proactive compliance where required. • Leading or participating in regulatory agency interactions and advocacy work regarding legislation relevant to this field. • Engage with relevant regulatory authorities, industry bodies, collaborative communities, and policymakers to shape the regulatory landscape for AI and P2P. • Lead the development and execution of regulatory strategies, identifying preferable market/s from which to operate, and to ensure the company’s readiness for compliance with relevant national and international regulations. • Collaborate with internal teams (e.g., R&D, legal, compliance) in both Tether and with our partners to integrate regulatory considerations into the design and deployment of AI models and technologies, as applicable. • Act as a thought leader both externally and within the organization, educating internal teams on regulatory issues, trends, and best practices in the AI and P2P space.

• Own the inference backbone behind QVAC's local AI stack • Ensure that local AI capabilities ship reliably and perform well across devices • Balance hands-on technical work with team coordination • 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 assess 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

• Work on deploying machine learning models to edge devices using llama.cpp, ggml, and onnx • Collaborate closely with researchers to assist in coding, training, and transitioning models from research to production environments • Integrate AI features into existing products

• You will own the inference backbone behind QVAC's local AI stack: • 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