Jobs at Tether.io

Supports daily finance operations by validating timesheets, employee expenses, and contractor invoices. Maintains accurate payment and reimbursement records, ensures policy compliance, resolves discrepancies, assists with payment processing, and contributes to financial reporting, audits, and process improvements. Requires strong attention to detail, organization, communication, and proficiency with spreadsheets and financial tools.

Build functional peer-to-peer applications and infrastructure with Pear and Bare, then create polished screen-share demos, code-along videos, guides, and interactive repositories. Translate cryptography, protocols, and distributed systems into accessible developer content. Collaborate with core engineering teams, technical influencers, and developer advocates to prototype applications and accelerate adoption of Tether’s decentralized technology ecosystem.

Architect and maintain GitHub-based CI/CD pipelines, test-driven deployments, Docker containerization, and automated release workflows. Manage JavaScript, TypeScript, and C++ package lifecycles; build cross-platform applications with CMake; and automate web, desktop, and mobile releases. Provision secure, scalable infrastructure using IaC tools while supporting Linux administration, networking, monitoring, troubleshooting, and release reliability across distributed teams.

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.

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.

As a Research Engineer Intern, you'll develop state-of-the-art LLM and multimodality models, optimize distributed training frameworks, and collaborate on the application of large models in business scenarios.

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.

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.

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.

As an AI Research Engineer, you will innovate in model compression techniques for large multimodal AI systems, focusing on efficiency and model deployment.

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.

Build a decentralized, serverless P2P search stack using Node.js. Implement and evaluate distributed indexing, DHTs, CRDTs, and networking (NAT traversal, encryption, multiplexing). Optimize protocols and high-concurrency networking code and work with the Holepunch stack components like hyperdht and hyperswarm.

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 performance, and advance cross-modal alignment and efficiency.

Design, build, and scale backend services and APIs in Node.js for high-availability financial and tokenization infrastructure. Work on blockchain integrations, token operations, permissions and transaction workflows, observability, deployment automation, and reliability improvements while collaborating cross-functionally to translate product requirements into secure, scalable systems.