Senior CUDA Engineer for High-Performance Inference

Fuse Energy; Greater London; On-site; GBP 120,000 - 160,000; Full time

Benefits offered by this job

Equity sign‑on bonus

Biannual bonus

Fully expensed tech

Office meals (breakfast & dinner)

Job summary

Fuse Energy is seeking an experienced CUDA Engineer to design and optimise low‑level GPU code for high‑throughput inference workloads. You will work on custom CUDA kernels, memory hierarchies, and mixed‑precision arithmetic to maximise throughput and minimise latency across GPU fleets.

The role focuses on profiling, kernel fusion, and performance‑driven optimisations with strong ownership of engineering quality and tests. London‑based office, competitive equity package.

Qualifications

• 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.

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.

Skills

CUDA

GPU architecture

CUDA C++

Profiling

Kernel optimization

Quantisation & mixed-precision

Multi-GPU knowledge

Attention kernels

Tools

PTX/SASS

Job description

Fuse Energy is seeking an experienced CUDA Engineer to design and optimise low‑level GPU code for high‑throughput inference workloads. You will work on custom CUDA kernels, memory hierarchies, and mixed‑precision arithmetic to maximise throughput and minimise latency across GPU fleets.

The role focuses on profiling, kernel fusion, and performance‑driven optimisations with strong ownership of engineering quality and tests. London‑based office, competitive equity package.