AI/ML Engineer and Full-Stack Developer
hammad986
B.Tech CSBS student, graduating in 2027. I build Python, generative AI and full-stack applications, from video question answering to document extraction.
Selected work: Video QA · Smart Doc AI · DealFlow CRM
7
Featured Projects
36
Credential Documents
6
Industry Internships
2
Windows Desktop Apps
Projects and Case Studies
Explore project scope, technologies and screenshots. Demo and source availability are shown on each project page.
CRM Pipeline Application
Freelancers and boutique agencies struggle with complex, expensive CRMs that lock data behind monthly subscriptions and slow multi-second cloud API calls.
✓ Client-side deal management with browser persistence
AI Document Intelligence
Manual document data entry from irregular PDFs, invoices, and contracts causes costly errors and takes upwards of 15 minutes per document.
✓ Document extraction into structured fields
Generative AI SaaS
Drafting winning client proposals requires hours of manual copywriting and scope estimation, leading to delayed pitches and lost deals.
✓ Proposal drafting with inline editing and PDF export
Systems Architecture & Philosophy
Production AI applications require more than static API wrappers. They demand robust schema normalization, low-latency client state, multi-model fallback redundancy, and verified execution proof.
I build end-to-end software systems that combine mathematical AI foundations with high-velocity product execution.
My portfolio covers document extraction, video question answering, computer vision and client-side web tools. Project pages describe the available implementation, screenshots and links. Benchmarks are included only when their methodology is documented.
Schema validation helps check output shape. It does not guarantee factual accuracy; source review remains necessary.
Client-side state and browser persistence support local workflows. Storage should not be assumed encrypted or suitable for sensitive data.
Python and OpenCV support video and image workflows. Performance depends on hardware, input and configuration.
An illustrative guide to the portfolio workflows. This is not a running AI service, model comparison or benchmark.
Trade-off: Complex layouts and uncertain fields need human review.
Credentials and Learning
A collection of credential documents across AI/ML engineering, data science, cloud architecture, government accreditations, and industry internships.
Course completions, internship documents and professional programs are listed separately. Issuer verification is linked only where a credential-specific URL is available.
Foundational ML mastery covering linear/logistic regression, cost function minimization, gradient descent optimization, and regularization under Professor Andrew Ng.
Enterprise generative AI workflows, model parameter tuning, prompt engineering, and multimodal foundation model deployment on Google Cloud Platform.
Applied generative AI models to complex enterprise datasets, generating executive dashboards, automated query reasoning, and business strategy insights.
Architectural Arsenal
Technologies, frameworks, mathematical foundations, and AI toolchains utilized to engineer scalable intelligent applications.
Industry Trajectory
A proven track record of shipping production code, Python automation pipelines, data extraction algorithms, and modern full-stack web applications.
Engineered state-of-the-art Generative AI applications, autonomous agents, LLM pipelines, prompt reasoning frameworks, and production-grade full-stack AI integrations.
Executed data analytics pipelines, exploratory data analysis, KPI dashboard reporting, and relational SQL query optimization.
Built applied machine learning workflows, model-centered product features, predictive analysis pipelines, and neural network experiments. Received official Letter of Recommendation.
Executed exploratory data analysis (EDA), data wrangling, model benchmarking, and created executive visualization dashboards for data-driven decisions.
Developed modular Python backends, automation scripts, OOP software architectures, and automated scraping/extraction pipelines.
Developed modern web application front-ends, responsive interfaces, database connectivity, and production-oriented software workflows.
Active open-source repositories covering autonomous AI agents, document intelligence models, computer vision utilities, and full-stack SaaS.
Public
Open Source
AI applications, dashboards, desktop tools and libraries
Active
Commit Activity
Public repositories and generative AI experiments
AI Engineering
Core Focus
Applied GenAI, autonomous systems and desktop utilities
Direct Engineering Contact
Reach out for full-stack AI engineering roles, product builds, generative AI pipelines, or technical consultations.
Available for software engineering roles, generative AI development, and scalable system architecture.
Primary Email
mdhammad2906@gmail.com