Machine Learning Systems Engineer

About the role

Join Tether and Shape the Future of Digital FinanceAt 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.Innovate with TetherTether 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.But that s just the beginning:Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.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.Why Join Us?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?About the jobWe are developing a highly scalable media intelligence platform that processes, analyzes, and structures large volumes of multimedia content across text, image, video, and audio. As a Senior Applied ML Engineer, you will architect and build the core backend systems that power media ingestion, processing workflows, metadata generation, AI-based analysis, semantic search, and retrieval across large media libraries.We are looking for a Senior Applied ML Engineer who can design, implement, optimize, and evaluate a production-grade moderation pipeline using open-source models.This role requires deep backend engineering expertise, strong system design capability, and practical experience integrating AI/ML systems into production workflows. You will work on complex media-processing pipelines, video/audio analysis, OCR, speech-to-text, embedding generation, vector search, multimodal model integrations, and high-throughput asynchronous workloads. You will collaborate closely with engineering leadership to define backend architecture, improve reliability and scalability, and guide other engineers in delivering secure, observable, and high-performance systems.ResponsibilitiesBackend Architecture & System OwnershipArchitect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies.Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution.AI/ML Integration & Model WorkflowsLead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows.Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies.Collaborate with ML engineers, data scientists, or external model providers to benchmark models