AI Research Engineer – Model Compression, Quantization

This is a fully remote position, open to applicants in Ireland.

📋 Description

• Spearhead advancements in model compression and the efficient deployment of sophisticated multimodal AI systems.

• Minimize model size and computational expenses while maintaining accuracy.

• Implement and enhance compression methods such as quantization, knowledge distillation, and pruning.

• Develop reliable compression pipelines and set performance and fidelity benchmarks.

• Provide scalable, low-memory, and low-latency AI solutions for edge devices.

⛳️ Requirements

• A degree in Computer Science or a related discipline.

• Preferably a PhD in NLP, Machine Learning, or a related area, with a strong history in AI research and development (including notable publications in A* conferences).

• Proficiency in PyTorch deep learning frameworks or equivalent alternatives.

• Practical experience with model quantization, encompassing both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).

• Research and practical experience in knowledge distillation for transforming large models into smaller, more efficient versions.

• Research and practical experience in model pruning for reducing large models into smaller, efficient counterparts.

• Strong understanding of neural network architectures and training methodologies, including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning strategies.

• Familiarity with C++ is advantageous, particularly for implementing low-level quantization kernels or optimizing inference processes.

🏝️ Benefits

• Access to an innovative product suite.

• Options for remote work.

• Opportunity to collaborate with global talent.

• Chance to make contributions in the fintech sector.