CUDA Engineer
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Job Description
CUDA Engineer writing and optimizing performance-critical GPU code at a renewable energy startup. Focusing on high-performance compute infrastructure to support AI applications.
Responsibilities:
- Write and optimise 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.
- Optimise memory access patterns and manage the memory hierarchy for maximum bandwidth utilisation.
- Implement quantisation-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 quantised and mixed-precision kernels.
- Solid grasp of parallel algorithm design and numerical precision tradeoffs.
- Nice to Have
- Experience with transformer/attention-style kernels or autoregressive decoding.
- Experience building high-performance GPU libraries from scratch.
- Background in HPC or other latency-critical performance engineering.
- Exposure to multi-GPU or multi-node kernel-level optimisation.
- Comfortable reading PTX/SASS to validate kernel efficiency.
Benefits:
- Competitive salary and an equity sign-on bonus.
- Biannual bonus scheme.
- Fully expensed tech to match your needs.
- Breakfast and dinner allowance for office based employees.
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