Senior GPU Performance Engineer (AI/ML Infrastructure)

crosstalent • Gibraltar

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AI Summary

Optimize GPU-accelerated deep learning models and infrastructure for large-scale training and serving. Design performance improvements, debug low-level GPU code, and scale workloads across distributed compute clusters. Contribute to post-training processes like reinforcement learning and fine-tuning.

Key Highlights

Optimize GPU performance for large-scale deep learning model training and serving

Design and implement improvements to training and serving infrastructure

Work with low-level GPU code (CUDA, C++) and distributed compute clusters

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Key Responsibilities

Design and implement performance optimizations for GPU-accelerated deep learning models

Debug and improve low-level GPU code (CUDA, C++) for training and inference pipelines

Scale GPU jobs across large-scale compute clusters using Slurm or Kubernetes

Analyze and optimize performance bottlenecks in distributed training and serving infrastructure

Contribute to post-training processes including reinforcement learning and fine-tuning

Technical Skills Required

Python CUDA PyTorch

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Benefits & Perks

Five weeks of paid leave

Comprehensive healthcare benefits (including vision and dental)

Visa support (H1B and OPT transfers)

Job Description

We are seeking an experienced GPU Performance Engineer with a strong background in Python and large-scale model training. In this role, you will design and implement improvements to our training infrastructure and directly contribute to technical decisions that optimize performance of our models. You will also work on post-training processes, including reinforcement learning and fine-tuning. Furthermore, you will contribute to improving the efficiency and scalability of our model serving infrastructure. Ideal Experience

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