AI System Optimization Intern

About Bitdeer:

Bitdeer Technologies Group (Nasdaq: BTDR) is a leader in the blockchain and high-performance computing industry. It is one of the world's largest holders of proprietary hash rate and suppliers of hash rate. Bitdeer is committed to providing comprehensive computing solutions for its customers.

The company was founded by Jihan Wu, an early advocate and pioneer in cryptocurrency who cofounded multiple leading companies serving the blockchain economy. Headquartered in Singapore, Bitdeer has deployed mining datacenters in the United States, Norway, and Bhutan. It offers specialized mining infrastructure, high-quality hash rate sharing products, and reliable hosting services to global users. The company also offers advanced cloud capabilities for customers with high demands for artificial intelligence.

Dedication, authenticity, and trustworthiness are foundational to our mission of becoming the world's most reliable provider of full-spectrum blockchain and high-performance computing solutions. We welcome global talent to join us in shaping the future.

What you will be responsible for:

• Support the development and optimization of compute operators for large AI models running on custom AI hardware (e.g., NPUs or tensor accelerators).
• Assist in designing and implementing parallel execution and memory access strategies to improve throughput and efficiency.
• Collaborate with senior engineers and hardware designers to explore hardware-software co-design techniques, focusing on chip architecture constraints and compiler/runtime behavior.
• Contribute to performance tuning and profiling of AI training and inference workloads by identifying bottlenecks in operators, compiler passes, and runtime execution.
• Learn and help integrate advanced compiler tools and frameworks such as TVM, MLIR, XLA, or LLVM into the AI model compilation pipeline.
• Explore and evaluate optimization strategies such as quantization, operator fusion, and multi-core parallelism to accelerate model execution.
• Stay updated with emerging AI workloads (e.g., LLMs) and support experiments to improve their performance on AI accelerator platforms.

How you will stand out:

• Currently pursuing a Master's degree in Computer Science, Electrical/Electronic Engineering, Automation, or a related field.
• Proficient in C/C++ and/or Python, with a good understanding of algorithms and data structures.
• Basic understanding of AI accelerators (e.g., NPUs, GPUs) and interest in computer architecture and microarchitecture.
• Exposure to topics like memory hierarchy, parallel computing, or low-precision computation is a plus.
• Familiar with deep learning frameworks such as PyTorch, TensorFlow, or MindSpore, including basic knowledge of their execution flow.
• Interest in or coursework related to compiler frameworks (e.g., TVM, MLIR, XLA, LLVM) and operator-level optimization is preferred.
• Understanding of or curiosity about LLMs and tools like TensorRT-LLM, VLLM, or ORCA is an added advantage.
• Strong willingness to learn, problem-solve, and contribute to a collaborative hardware-software optimization environment.

What you will experience working with us:

• A culture that values authenticity and diversity of thoughts and backgrounds;
• An inclusive and respectable environment with open workspaces and exciting start-up spirit;
• Fast-growing company with the chance to network with industrial pioneers and enthusiasts;
• Ability to contribute directly and make an impact on the future of the digital asset industry;
• Involvement in new projects, developing processes/systems;
• Personal accountability, autonomy, fast growth, and learning opportunities;
• Attractive welfare benefits and developmental opportunities such as training and mentoring.

Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.