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AI Inference Engineer – QVAC

🕒 2 days ago

🇨🇴 Colombia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

Where this job comes from

Posted on Tether.to's careers page, not through a job board

First seen by Remote Rocketship 2 days ago

Still open on Tether.to's site. Checked 53 minutes ago.

Logo of Tether.to

Tether.to

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

• Own the inference backbone behind QVAC's local AI stack • Engineer the C++ systems layer for fast, reliable, and predictable model execution on user hardware • Optimize startup behavior, memory pressure, throughput, latency, and long-session stability • Define and evolve core abstractions for inference features • Deploy machine learning models to edge devices using llama.cpp and ggml • Port and enhance inference engines to run efficiently across different hardware • Collaborate with researchers on coding, training, and transitioning models from research to production • Integrate AI features into existing products • Enable private, fast, on-device AI without relying on cloud infrastructure

🎯 Requirements

• Strong programming skills in C++ • Strong experience with Llama.cpp and ggml inference engines • Experience with at least one GPU framework: CUDA, Vulkan, Metal, or OpenCL • Good understanding of deep learning concepts and model architectures • Experience with transformers, LLMs, and diffusion models • Demonstrated ability to rapidly assimilate new technologies and techniques • A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D • Bonus: experience training or fine-tuning an LLM • Bonus: experience productionizing models • Bonus: research experience in new model architectures • Bonus: experience with distributed systems • Javascript experience

🏖️ Benefits

• Remote work from locations worldwide • Opportunity to collaborate with a global team • Work on private, on-device AI experiences • Opportunity to contribute to innovative fintech, blockchain, AI, and peer-to-peer technology products

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