AI Efficiency Research Intern - Model Optimization

Bitdeer Technologies Group; Singapore; On-site; SGD 17,000 - 28,000; Full time

Benefits offered by this job

Training and mentoring

Job summary

Bitdeer is seeking a motivated intern to join its AI Lab in Singapore, focusing on making large AI models cheaper and faster to serve. You will work on quantization, sparsity, pruning, and serving-time optimizations across hardware and software stacks, and build a solid evaluation framework.

The role is designed as a 3–6 month project with ownership and presentation responsibilities, with the potential to convert the internship based on outcomes and impact.

Qualifications

• Undergrad, Master's or PhD candidates in CS/EE/Math or related field; 3–6 months, full-time preferred.
• Strong Python programming and hands-on PyTorch experience.
• Coursework or research in model efficiency: quantization, sparsity/pruning, speculative decoding, or KV-cache methods.
• Depth in at least one project/paper/open-source work you can explain end-to-end.
• Solid understanding of transformer internals and rigorous evaluation with solid baselines.

Responsibilities

• Make models cheaper and faster to serve without sacrificing quality; implement/adapt quantization, pruning, and related methods.
• Build evaluation discipline to defensibly claim improvements (e.g., 2× throughput).
• Own and present a single well-defined project within 3–6 months; potential conversion based on performance.

Skills

Python

Transformer internals

Ownership mentality

Education

CS/EE/Math or related field (Undergrad/Master/PhD)

Tools

PyTorch

Quantization

Sparsity/Pruning

Serving-time attention / KV-cache

Job description

Bitdeer is seeking a motivated intern to join its AI Lab in Singapore, focusing on making large AI models cheaper and faster to serve. You will work on quantization, sparsity, pruning, and serving-time optimizations across hardware and software stacks, and build a solid evaluation framework.

The role is designed as a 3–6 month project with ownership and presentation responsibilities, with the potential to convert the internship based on outcomes and impact.