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Waleed Arif

Waleed Arif

AI Engineer with 2+ years of experience building and deploying LLM, Generative AI and Computer Vision solutions

Talent
LahoreMember since August 24, 2026
PythonJavaScriptJavaPandasScikit-learnPyTorchTensorFlowKerasLLMsHugging Face TransformersFlaskData PreprocessingComputer VisionRAGProblem-Solving
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PythonJavaScriptJavaPandasScikit-learn

About

AI Engineer with 2+ years of experience building and deploying LLM, Generative AI and Computer Vision solutions to solve real-world business challenges using advanced AI/ML technologies. Deep proficiency in Python, LoRA/PEFT fine-tuning, RAG pipelines, and vLLM inference serving, with strong foundations in data preprocessing, model training and deployment. Strong communication and problem-solving abilities, proven ability to work independently and collaborate with cross-functional teams to deliver end-to-end AI solutions from concept to production at scale.

Experience

AI/ML Engineer at TekkDev (2025-11 – Present)

  • Fine-tuned open-source LLMs via LoRA/PEFT for domain adaptation, matching full fine-tuning performance with minimal trainable parameters and reduced GPU memory overhead.
  • Deployed LLM inference on-premise GPU servers using vLLM, achieving a 3–5x throughput boost with optimized high-concurrency handling and zero downtime.
  • Engineered scalable inference pipelines supporting simultaneous multi-user sessions with zero downtime and enterprise-grade reliability.
  • Developed Computer Vision models reaching 90–95% accuracy using advanced image preprocessing and augmentation techniques for stable training under limited data & compute.
  • Deployed CV models with robust multi-user concurrency management and enterprise-grade security controls for reliable real-time production inference.

AI Engineer at Sygnls (2024-09 – 2026-03)

  • Optimized processing of 10TB+ enterprise datasets through incremental chunking, reducing re-chunking time by 80%.
  • Built and deployed RAG applications on Azure ML Studio with Azure AI Search, improving query response times by 30% and document retrieval accuracy across large enterprise datasets.
  • Implemented CI/CD pipelines with Azure DevOps and automated testing, reducing deployment time across 3+ ML projects.
  • Developed Flask-based RESTful APIs integrating AI models into responsive web interfaces, serving multiple concurrent enterprise users.
  • Collaborated with cross-functional data engineering and product teams to design and maintain scalable, production-grade ML pipelines.

Education

Bachelor of Science in Computer Science – National University of Sciences and Technology (NUST) (2020-09 – 2024-06)

Skills

Generative AI and Computer Vision solutions

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