Senior ML Infrastructure Engineer, VE Algorithms

What you'll do

• 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 the full compilation stack from high-level graph capture to target hardware.
• Build and maintain experimentation tooling, dashboards, and scalable CI/CD pipelines for multi-GPU workflows.
• Develop infrastructure for training, adapting, and deploying large-scale generative models.
• Benchmark and prototype algorithmic choices to ensure compatibility with existing training and deployment infrastructure.

What we're looking for

• BS in Electrical Engineering, Computer Science, or a related field with a focus on machine learning.
• Minimum of 3 years of industry experience.
• Experience training and adapting large language models (LLMs).
• Advanced fluency in PyTorch.
• Excellent programming skills in Python or C++.
• Experience with distributed training of large models.
• Strong machine learning fundamentals.
• Experience working with large cross-functional and diverse teams.