Systems Engineer Hybrid
4 weeks ago
Job Description ML System Performance Engineer
I am seeking an experienced ML System Performance Engineer who has a track record of using ML models to carry out performance analysis on NPUs, CPUs or GPUs and to be based in Cambridge working on a hybrid basis. Must have a track record of utilising ML models to investigate simulators for system performance analysis. E.g., bottlenecks, latency, workload analysis, changes and debugging.
Primary Responsibilities
Working closely with the modelling and performance team to apply ML models to investigate simulations and carry out performance analysis on NPUs (Neural Processing Unit).
Required Experience
Masters or PhD in Computer Science, Electronic Engineering or similar.
At least 4 years of industry experience working with ML models for system performance analysis.
Strong background with CNN and Transformer Architecture.
Experience with ML frameworks like Pytorch/Tensorflow and programming languages C++ and Python.
Desired Experience
Industry experience at leading NPU, CPU, GPU, semiconductor manufacturer.
Knowledge of system modelling/simulation technology, such as SystemC, Gem5, Simics, QEMU etc.
What’s on offer
Competitive Salary (£80k-120k)
Hybrid working (1-2 day’s onsite minimum, preference for more on-site if local)
Annual Bonus
25 days holiday
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