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I’m Yakhyokhuja (Yakhyo) Valikhujaev, an AI/ML & MLOps Engineer with 6+ years of industry and research experience focused on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Vision-Language Models (VLMs), and scalable MLOps infrastructure.

Professional Background

I hold a Master’s degree in Computer Engineering from Gachon University, where I specialized in computer vision and deep learning applications. Currently, I work as an MLOps Engineer at Thaki Cloud, designing and maintaining Kubernetes-based ML platforms for distributed training and inference workloads.

My expertise spans fine-tuning and deploying transformer architectures, building Kubernetes clusters, and automating model training and deployment across cloud and on-prem environments. I focus on developing production-ready ML systems that solve real-world problems across various industries.

Through this platform, I share insights from my journey in machine learning engineering, document technical challenges and solutions, and contribute to the broader ML community. I also maintain a YouTube channel where I create programming tutorials.

Technical Interests

My primary areas of focus include:

  • LLMs & RAG: LoRA/PEFT fine-tuning, retrieval pipeline design, vLLM-based inference orchestration
  • MLOps & Infrastructure: Kubernetes cluster orchestration, workload scheduling, resource management, CI/CD pipelines
  • Conversational AI: Voice-to-voice AI agents with ASR, LLMs, and TTS pipelines
  • Multimodal AI: Vision-Language Models, OCR, object detection, tracking, video action recognition
  • Generative AI: Diffusion Models, GANs, DeepFakes, image-to-video generation
  • Edge Deployment: Model pruning, quantization, on-device inference optimization

Continuous Learning

I’m committed to staying current with the latest developments in ML/AI. Some technical books that have shaped my approach include:

  • Designing Machine Learning Systems by Chip Huyen (2022)
  • Fluent Python (2nd Edition) by Luciano Ramalho (2021)
  • Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann (2020)
  • Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron (2017)

Beyond Work

When I’m not coding, I enjoy swimming, hiking, and spending time with friends. I have a deep appreciation for mathematics and physics, and I’m interested in pursuing a PhD in the future if I find the right research opportunity that aligns with my interests in ML/AI.

I also solve algorithmic challenges on LeetCode, contribute to open-source projects, and create programming tutorials on my YouTube channel, where I’ve published courses on Python, C++, and Java for Uzbek-speaking learners.

Get in Touch

I’m always interested in discussing ML engineering, potential collaborations, or interesting technical challenges. I’m particularly open to joining open-source projects or research initiatives that align with my interests in LLMs, MLOps, and AI infrastructure.

Feel free to reach out via email or connect with me on LinkedIn.

“Expose yourself to your biggest fear; after all, if someone else can do it, so can you.”