Open to ML/AI opportunities

Shehryar Irshad

AI & ML Enthusiast

Building a strong foundation in AI engineering through hands-on work in NLP, deep learning, and machine learning workflows.

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// about

From Curiosity to AI Engineering

Learning in public through practical, real-world implementation.

Shehryar Irshad
terminal
$ whoami
> shehryar_irshad

$ cat skills.txt
> python, nlp, transformers,
> pytorch, data_analysis

$ echo $STATUS
> learning, building, improving

I'm Shehryar Irshad, an AI and Machine Learning enthusiast with a non-technical academic background in International Relations, currently based in Islamabad, Pakistan, and focused on building a strong foundation in AI engineering.

My journey started from curiosity about how large language models work, which led me into hands-on learning in NLP, deep learning, and data analysis.

I'm currently developing practical skills in transformer models, machine learning workflows, and deployment while working on real-world projects beyond tutorials.

I'm pursuing a Bachelor's Degree in International Relations and Affairs at the National University of Modern Languages (NUML), integrating research discipline with hands-on technical learning in AI.

I'm actively seeking opportunities as an ML Engineer or AI Engineer where I can contribute, learn, and grow in production-level AI systems.

1

Current Internship

3

Focus Areas

10+

Hands-on Projects

Daily

Learning Mode

// projects

What I've Built

A selection of AI-powered products and tools.

NeuroChat

An enterprise LLM chatbot platform with multi-model orchestration, RAG pipelines, and real-time streaming. Handles 50k+ concurrent conversations.

ReactPythonLangChainRedisPostgreSQL

VisionLab

Computer vision toolkit for real-time object detection, image segmentation, and visual search. Deployed across 200+ edge devices.

PyTorchOpenCVFastAPIDockerONNX

CodeSensei

AI-powered code reviewer that catches bugs, suggests optimizations, and enforces style guides. Integrated with GitHub Actions.

TypeScriptGPT-4GitHub APINext.jsVercel

FlowML

ML pipeline orchestrator for training, evaluation, and deployment. Supports distributed training across multi-GPU clusters.

PythonKubernetesApache AirflowGogRPC

PixelForge

AI image generation platform with fine-tuning, inpainting, and style transfer. Serves 10k+ generations daily.

Stable DiffusionReactNode.jsAWSS3
// skills

Skills & Learning Focus

Core strengths and actively developing capabilities in AI engineering.

AI / Machine Learning

Python88%
PyTorch (learning)65%
Transformers (learning)62%
Natural Language Processing74%
Data Analysis78%

Web / Tools

Git & GitHub82%
Basic JavaScript56%
APIs (REST basics)61%

Other

Problem Solving86%
Research Skills84%
Self-learning & Adaptability90%
// experience

Experience & Growth

Internship work and practical progression toward production-level AI engineering.

Mar 2026 — Present

ID Sports Ventures

Intern: Computer Vision Engineer

Supporting computer vision-focused work while building practical engineering habits across data handling, experimentation, and model development workflows.

PythonComputer VisionOpenCVPyTorch
2025 — Present

Self-Driven Learning

AI/ML Project Builder

Actively building experience through self-driven learning, coursework, and hands-on projects in machine learning and AI, including practical implementations in NLP, model training basics, and data handling.

NLPTransformersData AnalysisGitHub
2022 — Present

National University of Modern Languages (NUML)

Bachelor's Degree, International Relations and Affairs

Academic foundation in International Relations that strengthened research, analysis, and communication skills, now applied to practical AI engineering growth.

ResearchAnalysisCommunicationAdaptability
Current Focus

Career Transition

Aspiring ML / AI Engineer

Transitioning from a non-technical academic background in International Relations toward professional-level AI engineering by prioritizing real-world problem solving and deployment concepts.

ML WorkflowsModel DeploymentREST APIsResearch
// blog

Writing & Thinking

Thoughts on AI engineering, ML systems, and building products.

LLM

Why RAG is Eating the AI World

Retrieval-Augmented Generation is becoming the default architecture for enterprise AI. Here's why it works and how to build one.

Mar 20268 min read
ML

Fine-Tuning vs. Prompting: A Practical Guide

When should you fine-tune a model versus engineering better prompts? I break down cost, performance, and maintenance trade-offs.

Jan 202612 min read
MLOps

Building ML Pipelines That Don't Break at 3AM

Lessons from running production ML systems. Monitoring, rollback strategies, and why you need feature stores.

Nov 20256 min read
CV

The State of Computer Vision in 2025

From YOLO to vision transformers — a survey of what's working in production computer vision systems today.

Sep 202510 min read
// contact

Let's Build Something

Open to ML/AI opportunities and collaborations.

shehryarirshad11@gmail.com
+92 3045106379 (Mobile)
Islamabad, Islāmābād, Pakistan
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