AI Research Engineer Model Serving Inference Remote Brazil

Join Tether and Shape the Future of Digital Finance

At Tether, we’re not just building products, 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. 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. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

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.

Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco‑friendly practices in state‑of‑the‑art, geo‑diverse facilities.

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.

Democratizing access to top‑tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.

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’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.

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.

Are you ready to be part of the future?

As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real‑world applications. You will work on a wide spectrum of systems, ranging from resource‑efficient models designed for limited hardware environments to complex, multi‑modal architectures that integrate data such as text, images, and audio.

We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands‑on, research‑driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments.

The ultimate goal is to enable high‑throughput, low‑latency, low‑memory footprint, and scalable AI performance that delivers tangible value in dynamic, real‑world scenarios.

• Design and deploy state‑of‑the‑art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource‑constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.

• Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource‑constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across…