Model Efficiency Research Scientist — AI Inference

Bitdeer (NASDAQ: BTDR); San Jose (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Bitdeer AI Lab is seeking a talented ML systems engineer to optimize large language model inference and deployment. You will push efficiency through quantization, sparsity, pruning, and related techniques, while maintaining accuracy and throughput.

You will collaborate on production-ready ML systems, apply advanced benchmarks, and contribute to cutting‑edge AI infrastructure within a fast-growing, globally engaged team.

Qualifications

• Hands‑on experience in LLM inference, model optimization, or ML systems.
• Strong programming ability in Python and deep familiarity with PyTorch.
• Experience with inference engines and deployment considerations.
• Deep understanding of transformer internals and model behavior.

Responsibilities

• Make models cheaper and faster to serve without sacrificing quality.
• Implement and adapt published efficiency methods and develop new optimizations.
• Build evaluation discipline to defend performance claims.

Skills

LLM inference

Model optimization

ML systems

Python

PyTorch

C++

CUDA

Triton

Transformer internals

Evaluation discipline

Education

Bachelor’s/Master’s/PhD in CS/EE

Tools

vLLM

SGLang

TensorRT-LLM

Job description

Bitdeer AI Lab is seeking a talented ML systems engineer to optimize large language model inference and deployment. You will push efficiency through quantization, sparsity, pruning, and related techniques, while maintaining accuracy and throughput.

You will collaborate on production-ready ML systems, apply advanced benchmarks, and contribute to cutting‑edge AI infrastructure within a fast-growing, globally engaged team.