Senior ML Infrastructure Engineer - VE Algorithms

In this role you will be technically hands on, with deep subject matter expertise in ML infrastructure, focusing on distributed and parallelized training of images and videos, and efficient utilization of training hardware. Optimize and profile training pipelines for large-scale visual pre-training across diffusion and auto-regressive architectures. Design and implement workload scheduling strategies for distributed training across clusters of thousands of GPUs. Profile and optimize across the full compilation stack — from high level graph capture through intermediate representations down to target HW. Build and maintain experimentation tooling, dashboards, and scalable CI/CD pipelines tailored to multi-GPU training workflows. BS in Electrical Engineering/Computer Science or a related field, with a focus on machine learning and minimum 3 years industry experience. Experience in training and adapting LLMs. Advanced fluency in PyTorch. Excellent programming skills in Python or C++ and experience contributing software to large projects. Experience with distributed training of large models. Strong Machine Learning fundamentals. Experience working with large cross-functional and diverse teams.

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