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Tether.to
Tether.to
11 – 50 Employees
CryptoFinanceFintech
Tether.to is a digital asset company focused on stablecoin infrastructure and blockchain-based payments. Its Tether tokens are designed to maintain a 1-to-1 value with corresponding fiat currencies and can be transferred across multiple blockchains, supporting digital transactions and cross-border payments. The company also publishes information about its assets and reserves and develops educational initiatives intended to expand understanding and use of digital assets, including in the Middle East, Turkey, and the Philippines. With its work spanning crypto, fintech, and finance, Tether.to contributes to the development of alternative financial infrastructure and stable digital currency applications.
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AI Research Engineer – Kernel and Inference Optimization, Remote Europe

Optimize GPU kernels, model serving, and inference systems for Tether’s blockchain-powered digital finance platform. Improve latency, throughput, and memory efficiency across mobile and edge devices.

EUEuropean UnionRemoteFull-timeMiddleSeniorEnglish RequiredAI Research ScientistMachine Learning Engineer
Flash

Description

  • Design and deploy model-serving architectures that maximize throughput, minimize latency, and use memory efficiently.
  • Improve inference performance across resource-constrained devices and edge platforms.
  • Set performance targets for latency, token response times, and memory footprint.
  • Build, execute, and monitor controlled inference tests in simulated and production environments.
  • Monitor latency, throughput, memory usage, and error-rate performance indicators.
  • Record iterative findings and compare results with established cross-platform benchmarks.
  • Develop test datasets and simulation scenarios for low-resource deployment conditions.
  • Evaluate computational efficiency and identify bottlenecks in serving pipelines.
  • Optimize batching, network delays, memory use, scalability, and reliability.
  • Work with cross-functional teams to integrate optimized serving and inference frameworks into production edge and on-device pipelines.
  • Establish success metrics, monitor performance continuously, and refine solutions iteratively.

Requirements

  • Degree in Computer Science or a related discipline.
  • PhD in NLP, Machine Learning, or a related field is preferred.
  • Demonstrated AI research and development experience, including strong publications at A* conferences.
  • Working knowledge of Metal Shading Language (MSL).
  • Ability to create custom compute shaders from the ground up.
  • Experience optimizing low-level kernels and inference on mobile devices.
  • Evidence of improving inference latency, throughput, and memory footprint for domain-specific applications.
  • Advanced understanding of modern model-serving architectures and inference optimization methods.
  • Strong experience writing GPU kernels for smartphones and other mobile devices.
  • Advanced knowledge of model-serving frameworks and inference engines.
  • Hands-on experience developing and deploying end-to-end inference pipelines on resource-constrained devices.
  • Ability to apply empirical research to serving challenges involving latency, computational bottlenecks, and memory limits.
  • Proficiency in designing evaluation frameworks and iterating on optimization approaches.
  • Experience with distributed inference systems, including tensor, pipeline, and expert parallelism.
  • Advanced understanding of the mathematics and architecture of Diffusion Models and Vision Transformers.
  • Knowledge of pruning, quantization, Flash Attention, KV cache, and speculative decoding with Eagle.

Benefits

  • Work remotely from anywhere in the world.
  • Collaborate with an international team.
  • Contribute to fintech, blockchain, artificial intelligence, and digital finance products.

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