AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited5 months ago
Remote, WorldwideSenior
Responsibilities
- Apply low-bit quantization to LLMs, VLMs, and other multimodal generative AI models while maintaining accuracy and output quality.
- Use knowledge distillation to transfer capabilities from larger teacher models to smaller student models across text, image, and audio inputs.
- Implement pruning methods that remove redundant parameters and attention heads while preserving task performance.
- Evaluate trade-offs among model size, latency, memory usage, throughput, and accuracy, and propose improvements based on empirical results.
- Research and apply mixed-precision quantization, adaptive pruning schedules, intermediate feature matching, and other advanced compression strategies.
- Build compression pipelines, establish performance and fidelity metrics, and address production inference bottlenecks for edge deployment.
- Stay current with model-compression research for multimodal and generative architectures.
- Document methodologies, experiments, and results to support reproducibility and collaboration.
- Author technical papers and publish model-compression research at top-tier conferences.
Requirements
- Bachelor’s degree in Computer Science or a related field; a PhD in NLP, Machine Learning, or a related field is preferred.
- Solid track record in AI research and development, ideally including publications at leading conferences.
- Hands-on experience with PyTorch or an equivalent deep learning framework.
- Experience with both Quantization-Aware Training and Post-Training Quantization.
- Research and practical experience using knowledge distillation to compress large models.
- Research and practical experience using model pruning to compress large models.
- Strong understanding of neural network architectures and training, including transformers, LLMs, VLMs, backpropagation, optimization, and fine-tuning.
- C++ experience is preferred, particularly for low-level quantization kernels or inference optimization.
Benefits
- Global remote work with collaboration across locations.
- Opportunity to work on advanced multimodal AI research and efficient edge deployment.
- Opportunity to publish findings at leading research conferences.
About Tether Operations Limited
Tether Operations Limited develops and issues reserve-backed digital tokens used by exchanges, wallets, payment processors, and merchants, most notably the USDT stablecoin available across multiple blockchains. Founded in 2014 and privately held, it earns revenue from token issuance, reserve management, and related services, and has expanded into tokenization, peer-to-peer communications (Keet), and Bitcoin mining. USDT is widely used in crypto trading and cross-border transfers, including in emerging markets.