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Senior AI Research Engineer, Model Inference (Remote)

Remote Full-time Live

This a Full Remote job, the offer is available from: United States, California (USA) 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. Innovate with Tether 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. 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 job: We are looking for an experienced AI Model Engineer with deep expertise in kernel development, model optimization, fine-tuning, and GPU acceleration. The engineer will extend the inference framework to support inference and fine-tuning for Language models with a strong focus on mobile and integrated GPU acceleration (Vulkan). This role requires hands-on experience with quantization techniques, LoRA architectures, Vulkan backend, and mobile GPU debugging. You will play a critical role in pushing the boundaries of desktop and on-device inference and fine-tuning performance for next-generation SLM/LLMs. Responsibilities:

  • Implement and optimize custom inference and fine-tuning kernels for small and large language models across multiple hardware backends.
  • Implement and optimize full and LoRA fine-tuning for small and large language models across multiple hardware backends.
  • Design and extend datatype and precision support (int, float, mixed precision, ternary QTypes, etc.).
  • Design, customize, and optimize Vulkan compute shaders for quantized operators and fine-tuning workflows.
  • Investigate and resolve GPU acceleration issues on Vulkan and integrated/mobile GPUs.
  • Architect and prepare support for advanced quantization techniques to improve efficiency and memory usage.
  • Debug and optimize GPU operators (e.g., int8, fp16, fp4, ternary).
  • Integrate and validate quantization workflows for training and inference.
  • Conduct evaluation and benchmarking (e.g., perplexity testing, fine-tuned adapter performance).
  • Conduct GPU testing across desktop and mobile devices.
  • Collaborate with research and engineering teams to prototype, benchmark, and scale new model optimization methods.
  • Deliver production-grade, efficient language model deployment for mobile and edge use cases.
  • Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.

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