Fuse Energy

Fuse Energy is a leading UK electricity supplier prioritizing affordability, service excellence, and sustainability through renewable energy projects and global reinvestment efforts.

Renewable Electricity

Utilities

11-50 (30)

Founded 2014

$78M raised

14 open positions

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CUDA Engineer

3 weeks, 1 day ago

United Kingdom

Full-time

Senior

AI Engineer

Software Development

C++ Sass

Apply Now

Fuse Energy

Fuse Energy is a leading UK electricity supplier prioritizing affordability, service excellence, and sustainability through renewable energy projects and global reinvestment efforts.

Renewable Electricity

11-50

Founded 2014

$78M raised

View All Jobs 14

Description

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 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 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.
Experience with transformer/attention-style kernels or autoregressive decoding (nice to have).
Experience building high-performance GPU libraries from scratch (nice to have).
Background in HPC or other latency-critical performance engineering (nice to have).
Exposure to multi-GPU or multi-node kernel-level optimisation (nice to have).
Comfortable reading PTX/SASS to validate kernel efficiency (nice to have).

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.

Interested in this position?

Apply directly on the company website

Apply Now

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