Jobs at Tether.io

Own end-to-end product design for digital wallets, from concept and prototyping through launch and iteration. Simplify complex crypto and self-custody experiences for new users, collaborate with product, engineering, research, and leadership, and raise design quality. The role also contributes to wallet strategy and requires rapid prototyping, strong visual and interaction design, and understanding of crypto networks, fees, and emerging financial users.

The Head of Regulatory Affairs will lead global regulatory strategies for Tether Data, focusing on AI and P2P technologies, promoting compliance and advocacy with regulatory bodies.

As a Senior UX Researcher at Tether, you'll lead UX research for both consumer and developer products, identify best practices, and support product decisions through clear, actionable insights.

The Internal Audit Manager will oversee the execution of internal audits, assess internal controls, and improve risk management practices within Tether's financial operations and technology systems.

The Financial Controller will manage financial reporting, accounting operations, and audits across multiple entities, ensure adherence to IFRS and US GAAP, and lead continuous improvement initiatives.

The Senior Business Analyst will evaluate mining investments, conduct due diligence, prepare financial models, and support M&A advisory for mining opportunities.

The Head of Licensing and Regulatory Authorisations at Tether will manage global licensing strategies, coordinate regional regulatory efforts, and ensure compliance with evolving legal frameworks in the digital assets space.

As an AI Inference Engineer, you will optimize C++ systems for AI model inference on edge devices, collaborating with researchers to deploy and enhance models while ensuring runtime stability and performance.

The Operations Associate/Senior Associate will manage trade confirmations, settlements, and operational processes for a multi-asset investment platform, requiring strong technical skills and attention to detail.

Lead end-to-end delivery of QVAC-powered AI implementations, acting as primary client contact. Translate business needs into deployment strategies, define roadmaps, coordinate product/engineering/legal stakeholders, manage risks and governance, and drive implementations from kickoff to production while producing executive reports and reusable documentation.

Drive strategic growth by managing and deepening relationships with blockchain foundations, design and execute partner-led growth projects, coordinate cross-functional initiatives, track and report project outcomes, and operate autonomously in a remote environment to expand real-world adoption of Tether assets.

Lead research and engineering for large-scale LLM and multi-modal pre-training: design architectures and tokenizers, curate massive datasets, run distributed training on thousands of GPUs, debug performance bottlenecks, and improve cross-modal alignment and efficiency.

The Financial Analyst manages vendor payments, tracks expenses, oversees receivables, performs reconciliations, prepares financial reports, and implements process improvements.

Drive end-to-end research and engineering on vision-language and multimodal models: data curation, training pipelines, post-training workflows (fine-tuning, distillation, RLHF), efficiency and deployment optimizations, distributed GPU training, evaluation frameworks, and publishing research.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

Join Tether as an AI Research Engineer focusing on model compression and quantization for AI systems. You'll innovate in reducing model footprint for multimodal architectures while applying advanced compression techniques, ensuring high performance on edge devices.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Drive research and engineering for large-scale LLM and multi-modal pre-training: design architectures, curate massive datasets, run distributed training on multi-node GPU clusters, optimize model efficiency and alignment, debug long training runs, and scale distributed training systems to improve cross-modal performance.