Tether Operations Limited
AI Research Engineer - Kernel & Inference Optimization(m/w/x)
Full-timeRemoteSenior
Zürich
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TETether Operations Limited
.AI Research Engineer (Model Compression & Quantization)(m/w/x)
Zürich
Full-timeRemoteSenior
AI/ML
Nejo AI Summary
Applying low-bit quantization to generative AI models for financial token integration. PhD in NLP/ML and A* publications required. Focus on model compression and efficient deployment.
Requirements
- Degree in Computer Science or related field
- PhD in NLP, Machine Learning, or related field
- Solid track record in AI R&D with A* publications
- Experience with PyTorch or equivalent frameworks
- Hands-on experience with model quantization (QAT and PTQ)
- Research and hands-on experience with knowledge distillation
- Research and hands-on experience with model pruning
- Solid understanding of neural network architectures and training
- Understanding of transformers (LLMs, VLMs), backpropagation, optimization, fine-tuning
- Familiarity with C++ (advantageous)
Tasks
- Drive innovation in model compression and efficient deployment
- Reduce model footprint and computational cost
- Apply low-bit quantization to generative AI models
- Maintain accuracy and output quality during quantization
- Leverage knowledge distillation for efficient multimodal reasoning
- Implement pruning techniques to reduce computational overhead
- Analyze trade-offs between model efficiency and accuracy
- Propose improvements based on empirical findings
- Research mixed-precision quantization and advanced compression strategies
- Stay current with the latest research in model compression
- Document methodologies, experiments, and results clearly
- Support reproducibility and internal collaboration
- Communicate results to stakeholders
- Author technical papers and publish findings
- Advance the field of model compression for multimodal AI
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- model quantization
- Quantization-Aware Training (QAT)
- Post-Training Quantization (PTQ)
- knowledge distillation
- model pruning
- neural network architectures
- transformers
- LLMs
- VLMs
- backpropagation
- optimization
- fine-tuning
- C++
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Tether Operations Limited and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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TETether Operations Limited
.AI Research Engineer (Model Compression & Quantization)(m/w/x)
Zürich
Full-timeRemoteSenior
AI/ML
Nejo AI Summary
Applying low-bit quantization to generative AI models for financial token integration. PhD in NLP/ML and A* publications required. Focus on model compression and efficient deployment.
Requirements
- Degree in Computer Science or related field
- PhD in NLP, Machine Learning, or related field
- Solid track record in AI R&D with A* publications
- Experience with PyTorch or equivalent frameworks
- Hands-on experience with model quantization (QAT and PTQ)
- Research and hands-on experience with knowledge distillation
- Research and hands-on experience with model pruning
- Solid understanding of neural network architectures and training
- Understanding of transformers (LLMs, VLMs), backpropagation, optimization, fine-tuning
- Familiarity with C++ (advantageous)
Tasks
- Drive innovation in model compression and efficient deployment
- Reduce model footprint and computational cost
- Apply low-bit quantization to generative AI models
- Maintain accuracy and output quality during quantization
- Leverage knowledge distillation for efficient multimodal reasoning
- Implement pruning techniques to reduce computational overhead
- Analyze trade-offs between model efficiency and accuracy
- Propose improvements based on empirical findings
- Research mixed-precision quantization and advanced compression strategies
- Stay current with the latest research in model compression
- Document methodologies, experiments, and results clearly
- Support reproducibility and internal collaboration
- Communicate results to stakeholders
- Author technical papers and publish findings
- Advance the field of model compression for multimodal AI
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- model quantization
- Quantization-Aware Training (QAT)
- Post-Training Quantization (PTQ)
- knowledge distillation
- model pruning
- neural network architectures
- transformers
- LLMs
- VLMs
- backpropagation
- optimization
- fine-tuning
- C++
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Tether Operations Limited and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Tether Operations Limited
Industry
FinancialServices
Description
The company pioneers a global financial revolution with blockchain solutions, enabling secure and instant digital token transactions.
Not a perfect match?
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