AI Research Engineer – Model Compression, Quantization

🔥 25 minutes ago

🇨🇭 Switzerland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Apply low-bit quantization to reduce model size and inference latency for generative AI models while maintaining accuracy and output quality • Use knowledge distillation to transfer capabilities from larger teacher models to smaller student models for multimodal reasoning across text, image, and audio • Implement pruning techniques to remove redundant parameters and attention heads • Analyze trade-offs among model size, latency, memory, throughput, and accuracy • Research and apply mixed-precision quantization and advanced compression strategies • Stay current with model-compression research for multimodal and generative architectures • Build robust compression pipelines and establish performance and fidelity metrics • Address bottlenecks in production inference • Develop scalable, low-memory, low-latency AI systems for edge devices such as smartphones • Document methodologies, experiments, and results for reproducibility and collaboration • Author technical papers and publish findings in conferences including NeurIPS, ICML, ICLR, CVPR, ACL, and AAAI

🎯 Requirements

• A degree in Computer Science or related field • PhD in NLP, Machine Learning, or a related field is ideally preferred • Solid track record in AI R&D with good publications in A* conferences • Experience with PyTorch deep learning frameworks or equivalent frameworks • Hands-on experience with Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ) • Research and hands-on experience with knowledge distillation • Research and hands-on experience with model pruning • Solid understanding of neural network architectures and training processes, including transformers, LLMs, VLMs, backpropagation, optimization, and fine-tuning techniques • Familiarity with C++ is a plus • Excellent English communication skills • Must specify the country from which they will work

🏖️ Benefits

• Remote work from anywhere in the world • Opportunity to collaborate with a global team and leading minds in fintech, AI, and blockchain • Work on innovative digital finance, blockchain, AI, and peer-to-peer technology products • Opportunity to author technical papers and publish findings in top-tier conferences • Professional and research collaboration opportunities