AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited5 months ago
Remote, WorldwideSenior
Responsibilities
- Apply low-bit and mixed-precision quantization, including QAT and PTQ, to reduce model size and inference latency while preserving accuracy.
- Use knowledge distillation to transfer capabilities from large teacher models to smaller multimodal student models across text, image, and audio inputs.
- Implement pruning methods to remove redundant parameters and attention heads without sacrificing task performance.
- Analyze model-size, latency, memory, throughput, and accuracy trade-offs across compression methods and propose empirical improvements.
- Build robust compression pipelines, establish performance and fidelity metrics, and address production inference bottlenecks.
- Research emerging compression techniques for multimodal and generative architectures, including adaptive pruning and intermediate feature matching.
- Document methodologies, experiments, and results to support reproducibility, internal collaboration, and stakeholder communication.
- Author technical papers and publish model-compression findings at leading AI conferences.
Requirements
- A degree in Computer Science or a related field is required; a PhD in NLP, Machine Learning, or a related field is preferred.
- A solid track record in AI research and development, ideally including publications at A* conferences.
- Experience with PyTorch or an equivalent deep learning framework.
- Hands-on experience with model quantization, including 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, including transformers, LLMs, VLMs, backpropagation, optimization, and fine-tuning.
- Familiarity with C++ is a plus, particularly for low-level quantization kernels or inference optimizations.
Benefits
- Remote work with a globally distributed team.
- Opportunity to conduct advanced AI research and publish at leading conferences.
- Work focused on efficient multimodal AI deployment for resource-constrained edge devices.
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.