Hi, I'm Kunjan Patel - Machine Learning Engineer at Google
I thrive on pushing AI performance limits, specializing in optimizing Diffusion models at scale with Jax on TPUs and GPUs. My passion is developing cutting-edge ML solutions and efficiently deploying them in high-performance computing environments.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Interned at vArmour and Tanium, building core software solutions and gaining a strong foundation in system design.
Currently optimizing Diffusion models at Google, pushing the boundaries of AI performance on TPUs and GPUs with Jax.
Can help others optimize deep learning models for accelerators and provide insights into building scalable ML infrastructure.
🚀 Career trajectory
Foundational Software Engineering
Began career as a Software Engineer at vArmour and Tanium, developing core software solutions and gaining a strong understanding of system design.
✦ vArmour
✦ Tanium
✦ Software Engineering
Transition to AI/ML
Moved into Machine Learning Engineering at Google, focusing on advanced AI models and accelerating their performance.
✦ Machine Learning
✦ AI/ML
Specialized in Large-Scale AI
Currently optimizing Diffusion models at scale on TPUs and GPUs using Jax, contributing to cutting-edge AI research and development.
✦ Diffusion Models
✦ Jax
✦ TPU
✦ GPU
✦ XLA
💪🏻 Superpowers
AI Performance Optimization
Expert in accelerating deep learning models
✦ Specializing in optimizing training and inference for Diffusion models.
✦ Leveraging Jax for efficient computation on XLA devices (TPU/GPU).
✦ Focused on achieving large-scale AI performance gains.
Scalable ML Systems
Building robust infrastructure for AI
✦ Experienced with Google Kubernetes Engine (GKE) for scalable deployments.
✦ Proficient in managing and orchestrating complex ML workloads.
✦ Ensuring reliable and efficient operation of AI systems.
Software Engineering Foundation
Strong roots in core programming principles
✦ Skilled in C++, Python, and Go for robust software development.
✦ Familiar with compiler technologies like LLVM and Pallas.
✦ Applying software engineering best practices to ML challenges.
I'm excited about
✦ Connecting with fellow AI researchers and engineers to share insights on model optimization.
✦ Exploring novel approaches to scaling AI training and inference efficiently.
✦ Discovering opportunities to collaborate on groundbreaking AI projects.
I can help with
✦ Share expertise on optimizing deep learning models for performance on accelerators.
✦ Provide insights into building scalable ML infrastructure using Kubernetes.
✦ Offer guidance on leveraging Jax for complex AI computations.
I would love your help on
✦ Learn about emerging research in novel AI architectures.
✦ Find collaborators for exploring new frontiers in generative AI.
✦ Get insights into real-world challenges in deploying large-scale AI models.