• Deep understanding of PyTorch, including writing custom modules, optimizing training, and debugging issues in large-scale models.
• Expertise in Developing Large Deep Learning Models from Scratch
• Proven ability to design, implement, and train complex deep learning architectures from the ground up.
• Hands-on experience in creating, cleaning, and maintaining high-quality datasets tailored for machine learning applications.
• Strong Software Engineering and Design Experience
• Proficient in software development best practices, including version control, testing, and code optimization.
• Familiarity with designing scalable and maintainable systems.
• Familiarity with generative architectures, particularly diffusion models, and an emphasis on posterior sampling methods.
• Knowledge of Transformer Architectures
• Experience building and training transformers, especially in applications involving 3D data.
• Scaling Models Across Large GPU Clusters
• Expertise in parallelizing models across multiple GPUs and optimizing distributed training pipelines.
• Cloud Infrastructure Expertise
• Experience setting up, managing, and optimizing cloud environments for machine learning workloads, including provisioning resources and managing costs.