AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited18 days ago
Remote, WorldwideSenior
Responsibilities
- Apply low-bit quantization to LLMs, VLMs, and other multimodal generative AI models while preserving 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 without materially reducing task performance.
- Evaluate trade-offs among model size, latency, memory, throughput, and accuracy across compression methods and propose empirical improvements.
- Research and apply mixed-precision quantization, adaptive pruning schedules, intermediate-feature distillation, and other advanced compression strategies.
- Build compression pipelines, performance and fidelity metrics, and solutions to production inference bottlenecks.
- 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 model-compression findings at leading research conferences.
Requirements
- Bachelor’s degree in Computer Science or a related field.
- Ideally, a PhD in NLP, Machine Learning, or a related field, with a strong AI research and development record and publications in A* 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 into smaller models.
- Research and practical experience using model pruning to compress large models into smaller models.
- Strong understanding of neural-network architectures and training, including transformers, backpropagation, optimization, and fine-tuning.
- Familiarity with C++ is preferred, particularly for low-level quantization kernels or inference optimization.
Benefits
- Remote work with a globally distributed team working from locations around the world.
- Opportunity to work on advanced multimodal AI compression and efficient edge-device deployment in a fintech and digital-asset company.
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.