AI Research Engineer – Kernel, Inference Optimization

🕒 May 19

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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

• Design and deploy model serving architectures that deliver high throughput and low latency • Ensure pipelines run efficiently across environments including resource-constrained devices and edge platforms • Establish clear performance targets for latency and memory usage • Build, run, and monitor controlled inference tests • Track key performance indicators like response latency and memory consumption • Document iterative results and compare outcomes against benchmarks • Analyze computational efficiency and diagnose bottlenecks in the serving pipeline • Work with cross-functional teams to integrate optimized frameworks into production pipelines • Define success metrics for improved performance and scalability

🎯 Requirements

• A degree in Computer Science or related field • Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences) • Knowledge of Metal Shading Language (MSL) • Comfort with writing custom compute shaders from scratch • Proven experience in low-level kernel optimizations and inference optimization on mobile devices • Contributions should have led to improvements in inference latency, throughput, and memory footprint for domain-specific applications • A deep understanding of modern model serving architectures and inference optimization techniques • Strong expertise in writing GPU kernels for mobile devices • Practical experience in developing and deploying end-to-end inference pipelines • Ability to apply empirical research to overcome challenges in model serving • Proficient in designing robust evaluation frameworks and iterating on optimization strategies • Experience with Distributed Inference Systems utilizing Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism • Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle)

🏖️ Benefits

• Work remotely from anywhere in the world • Opportunity to innovate in the fintech space • Collaborate with global talent • Competitive compensation packages • Flexible work arrangements