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 multimodal student models across text, image, and audio inputs.
- Implement pruning techniques to remove redundant parameters and attention heads without sacrificing task performance.
- Analyze efficiency-versus-accuracy trade-offs across quantization, distillation, and pruning methods and propose empirical improvements.
- Research and apply mixed-precision quantization, adaptive pruning schedules, intermediate feature matching, and other compression strategies.
- Build compression pipelines, establish performance and fidelity metrics, and address production inference bottlenecks.
- Document methodologies, experiments, and results to support reproducibility and collaboration.
- Author technical papers and publish model-compression research in top-tier AI conferences.
Requirements
- Bachelor’s degree in Computer Science or a related field.
- Solid track record in AI research and development, with strong publications in leading conferences; a PhD in NLP, Machine Learning, or a related field is preferred.
- Hands-on experience with PyTorch or an equivalent deep learning framework.
- Hands-on experience with Quantization-Aware Training and Post-Training Quantization.
- Research and hands-on experience with knowledge distillation for model compression.
- Research and hands-on experience with model pruning for model compression.
- Strong understanding of neural network architectures and training, including transformers, LLMs, VLMs, backpropagation, optimization, and fine-tuning.
- Familiarity with C++ is a plus, particularly for low-level quantization kernels or inference optimization.
Benefits
- Remote work with a globally distributed team.
- Opportunity to conduct applied AI research and publish findings in leading conferences.
- Work on efficient multimodal AI systems targeting resource-constrained edge devices.
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.