Research Kernel Engineer

About Bitdeer

Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud. It provides comprehensive Bitcoin mining solutions to its customers. Beyond designing leading-edge ASIC chips and manufacturing mining rigs, the group manages complex processes throughout the value chain, including equipment procurement, logistics, data center design and construction, equipment management, and network and facility operations. Additionally, Bitdeer offers advanced cloud capabilities to customers with high demands for artificial intelligence. Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio and deploys Bitcoin mining and high-performance computing (HPC) data centers in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.

About Bitdeer AI Lab

Bitdeer AI Lab is a frontier AI lab under Bitdeer, a global-leading computing power solutions provider. Guided by long-termism, the lab is dedicated to exploring the frontiers of artificial intelligence with ambition, courage, and determination to build technologies that can truly change the world. The mission is to convert energy into intelligence that people can afford to use. Inference is central to this mission: every product developed adheres to economic constraints, dictating what gets built. The lab works from the ground up, owning power and data centers and turning them into tokens, while continuously investing in and expanding the underlying infrastructure.

What You Will Be Responsible For

• Writing and optimizing CUDA/Triton kernels for new quantization schemes, sparsity patterns, attention variants, and speculative decoding strategies produced by the team’s research.
• Performing performance attribution across the serving path, including roofline analysis and identifying which kernels dominate under specific traffic patterns.
• Adapting published methods whose reference implementations are too slow for production use, making them viable for our specific models and traffic patterns.
• Building the measurement basis relied upon by the rest of the team, defining your own metrics before optimization, and being able to clearly articulate what a measurement proves and what it doesn’t.

How You Will Stand Out

• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field, with hands-on experience in GPU programming, high-performance computing, or ML systems.
• Proficiency in CUDA and/or Triton, with concrete examples of kernels you have written or meaningfully optimized.
• Strong Python and C++ skills.
• Working knowledge of GPU architecture and memory hierarchy, including occupancy, memory coalescing, tensor cores, warp-level primitives, and the ability to profile these using tools like Nsight Compute / Systems.
• Hands-on experience optimizing inference-critical paths such as attention, GEMM, normalization, sampling, or KV-cache management.
• Comfortable implementing methods without reference implementations, working from papers, notebooks, or whiteboards.
• Experience with inference engines like vLLM, SGLang, or TensorRT-LLM, including writing custom kernels or extensions for them.
• Compiler or IR-level experience (MLIR, TVM, TorchInductor), or experience with distributed serving (tensor/pipeline parallelism).
• Publications at top-tier systems venues, or substantial open-source contributions to inference or GPU computing projects.

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 an exciting start-up spirit.
• A fast-growing company with the opportunity to network with industry pioneers and enthusiasts.
• The chance to contribute directly and make an impact on the future of the digital asset industry.
• Involvement in new projects and developing processes/systems.
• Personal accountability, autonomy, fast growth, and learning opportunities.
• Attractive welfare benefits and developmental opportunities such as training and mentoring.