Ai Research Engineer

Join Tether and Shape the Future of Digital Finance
Our cutting‑edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve‑backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
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Tether Data: Fueling breakthroughs in AI and peer‑to‑peer technology, we reduce infrastructure costs and enhance global communications with cutting‑edge solutions like KEET , our flagship app that redefines secure and private data sharing.
Tether Education : Democratizing access to top‑tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Our team is a global talent powerhouse, working remotely from every corner of the world. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Your work will optimize decision‑making and adaptive behavior to deliver enhanced intelligence, improved performance, and domain‑specific capabilities for real‑world challenges. You will work across a broad spectrum of systems, including resource‑efficient models designed for limited hardware environments and complex multi‑modal architectures that integrate data such as text, images, and audio.
You will adopt a hands‑on, research‑driven approach to developing, testing, and implementing novel reinforcement learning algorithms and training frameworks. Your responsibilities include curating specialized simulation environments and training datasets, strengthening baseline policy performance, and identifying as well as resolving bottlenecks in the reinforcement learning process. Identify and curate high‑quality simulation environments and training datasets that are tailored to specific domain challenges. A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Proven experience with large‑scale reinforcement learning experiments, including online RL techniques such as Group Relative Policy Optimization (GRPO), is essential. Your contributions should have led to measurable improvements in domain‑specific decision‑making and overall policy performance.
Deep understanding of reinforcement learning algorithms is required, including state‑of‑the‑art online RL methods and other gradient‑based optimization approaches like policy gradients, actor‑critic, and GRPO. Practical experience in developing RL pipelines, from simulation and online training to post‑training evaluation and deploying RL‑based solutions in production environments is expected.
Demonstrated ability to apply empirical research to overcome reinforcement learning challenges such as sample inefficiency, exploration‑exploitation tradeoffs, and training instability. All our recruiters have verified LinkedIn profiles. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.