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About the Role
Fuse Energy is expanding into high-performance compute infrastructure at the intersection of energy and AI, optimizing power-dense GPU workloads. We are seeking a CUDA Engineer to write and optimize low-level GPU code for inference workloads, focusing on SMs, warps, and memory hierarchies to maximize throughput.
Responsibilities
- Write and optimize custom CUDA kernels for core transformer inference operations.
- Profile kernels to identify and eliminate bottlenecks in occupancy, memory throughput, and warp divergence.
- Apply kernel fusion to reduce memory round-trips and launch overhead across inference pipelines.
- Optimize memory access patterns and manage the memory hierarchy for maximum bandwidth utilization.
- Implement quantization-aware kernels and mixed-precision arithmetic to reduce latency and memory footprint.
- Build and tune caching mechanisms for efficient autoregressive decoding.
- Tune kernel launch configurations for target GPU architectures.
- Benchmark kernels against existing baselines and drive measurable throughput and latency improvements.
- Write tests for CUDA code to catch performance and correctness regressions.
- Maintain internal CUDA libraries and contribute to team coding standards and documentation.
Requirements
- 4+ years writing production CUDA code, with a track record of shipping performance-critical kernels.
- Deep understanding of GPU microarchitecture, warps, occupancy, register pressure, and memory hierarchy.
- Strong CUDA C++ skills, including streams and asynchronous execution.
- Hands-on experience profiling to diagnose compute-bound vs. memory-bound bottlenecks.
- Experience with kernel fusion, memory coalescing, and avoiding warp divergence.
- Experience writing quantized and mixed-precision kernels.
- Solid grasp of parallel algorithm design and numerical precision tradeoffs.
Skills
- CUDA
- GPU microarchitecture
- CUDA C++
- Streams
- Asynchronous execution
- Kernel fusion
- Memory coalescing
- Warp divergence
- Quantized kernels
- Mixed-precision kernels
- Parallel algorithm design
- Transformer kernels
- Autoregressive decoding
- HPC
- Multi-GPU optimization
- Multi-node kernel optimization
- PTX
- SASS
Experience Level
- 4+ years writing production CUDA code
Benefits
- Competitive salary
- Equity sign-on bonus
- Biannual bonus scheme
- Fully expensed tech to match your needs
- Breakfast and dinner allowance for office based employees
About the Company
- Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast.
- We're combining first-principles thinking with cutting-edge technology to build a radically better energy system.
- We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.
- As data centers become one of the largest and fastest-growing sources of electricity demand, Fuse is expanding into high-performance compute infrastructure that sits at the intersection of energy and AI - optimising how power-dense GPU workloads are scheduled, cooled, and balanced against grid conditions in real time.