AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited2 days ago
Remote, WorldwideSenior
Responsibilities
- Apply low-bit and mixed-precision quantization to LLMs, VLMs, and other multimodal generative AI models while preserving accuracy and output quality.
- Use knowledge distillation to transfer capabilities from large teacher models to smaller student models across text, image, and audio inputs.
- Implement pruning methods to remove redundant parameters and attention heads while maintaining task performance.
- Evaluate trade-offs among model size, latency, memory, throughput, and accuracy, and propose improvements based on empirical results.
- Build compression pipelines, establish performance and fidelity metrics, and address production inference bottlenecks on edge devices.
- Research advanced methods such as adaptive pruning schedules and intermediate feature-matching distillation.
- Document methodologies, experiments, and results to support reproducibility and collaboration.
- Author technical papers and publish model-compression research at top-tier conferences.
Requirements
- Degree in Computer Science or a related field.
- Strong AI research and development background, ideally including a PhD in NLP, Machine Learning, or a related field and publications at A* conferences.
- Experience with PyTorch or an equivalent deep learning framework.
- Hands-on experience with both 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 preferred, particularly for low-level quantization kernels or inference optimizations.
Benefits
- Remote work from locations around the world.
- Opportunity to work on multimodal AI research and efficient deployment for resource-constrained edge devices.
- Opportunity to publish findings at leading AI and machine learning 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.