AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited5 months ago
Remote, WorldwideSenior
Responsibilities
- Apply low-bit quantization to LLMs, VLMs, and other generative AI models while maintaining accuracy and output quality.
- Use knowledge distillation to transfer capabilities from larger teacher models to smaller student models for efficient multimodal reasoning across text, image, and audio inputs.
- Implement pruning techniques to remove redundant parameters and attention heads without sacrificing task performance.
- Analyze trade-offs among model size, latency, memory, 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 robust compression pipelines and establish performance and fidelity metrics for production inference.
- Stay current with model-compression research for multimodal and generative architectures.
- Document methodologies, experiments, and results to support reproducibility, collaboration, and stakeholder communication.
- Author technical papers and publish findings in leading AI research conferences.
Requirements
- Bachelor's degree or higher 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, including strong publications in top-tier conferences.
- 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 compressing large models.
- Research and hands-on experience with model pruning for compressing large models.
- Strong understanding of neural network architectures and training processes, including transformers, LLMs, VLMs, backpropagation, optimization, and fine-tuning.
- Familiarity with C++ is preferred, particularly for low-level quantization kernels or inference optimizations.
Benefits
- Remote work from locations around the world.
Categories
AI ResearchML Engineering
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.