Machine Learning Systems Engineer

🕒 May 28

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Tether.to

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

₿ Crypto

💳 Fintech

💸 Finance

Crypto • Fintech • Finance

Tether. to is a leading digital asset company that pioneers the use of stablecoins in the blockchain space. As the most widely adopted stablecoin, Tether tokens are designed to be pegged 1-to-1 with fiat currencies, offering a stable digital asset option for users. The platform facilitates these token transactions across multiple blockchains, enhancing cross-border transactions while maintaining transparency with daily records of total assets and reserves. Tether's initiatives include educational programs promoting digital asset usage, especially targeting regions like the Middle East, Turkey, and the Philippines. Tether thus positions itself as a disruptor in the traditional financial system by enabling a stable, efficient method of handling transactions in the digital currency world.

📋 Description

• Architect, build, and operate scalable backend services for a media intelligence platform • 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, and model-serving workflows • 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

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience • 5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services • Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations • 3+ years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs • Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis • Practical experience with production model optimization, especially for image, video, embedding, or multimodal models • Experience mentoring engineers, leading technical discussions, and influencing architectural decisions

🏖️ Benefits

• Opportunity to collaborate with a global team • Work on cutting-edge technologies • Flexible working arrangements