a
alii_shahzad

Ali S

@alii_shahzad

Software Engineer

Pakistan
Englisch, Urdu
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I am a software engineer with experience in developing AI-driven tools and API integrations. I have worked on projects involving machine learning, natural language processing, and audio processing. I am skilled in using technologies like FastAPI, Qdrant, Langraph, and Azure AI.... Mehr lesen

Kompetenzen

a
alii_shahzad
Ali S
offline • 
Durchschnittliche Antwortzeit: 75 Stunden

Meine Dienstleistungen

KI-Integrationen
I will build autonomous multi agent systems using langgraph, langchain
Ab90 $ / ProjektWeitere Details
Automatisierungen und Agenten
I will develop ai voice agents with vapi, livekit, fastapi
Ab50 $ / ProjektWeitere Details

Portfolio

Arbeitserfahrung

Software Engineer

APIMatic.io • Vollzeit

May 2023 - Present • 3 yrs

Engineered AI-driven Model Context Protocol (MCP) tools, servers, and chatbot context plugins for enterprise clients including PayPal and Shell, achieving one-shot SDK integration results with modern coding assistants. Developed the OpenAPI Specification (OAS) importer alongside APIMatic's VS Code extension and GitHub application to streamline the validation and importing of API specifications.

Machine Learning Engineer

108ai • Vollzeit

Nov 2022 - May 2023 • 6 mos

Developed an intelligent legal AI assistant leveraging Qdrant, Langraph, and Azure AI for RAG workflows. Implemented FastAPI for scalable API development and improving legal document processing. Worked on integrating LLMs for advanced document comprehension and retrieval and implemented chunking for Legal Documents.

Machine Learning Engineer

Rapidev NSTP • Teilzeit

May 2022 - Aug 2022 • 3 mos

Built a Transformer-based suspect matching system integrating audio enhancement, source separation, and speaker verification with Wav2Vec 2.0 and SpeechBrain. Designed an optimized audio pipeline for ASR and speaker identification using log-mel spectrograms, MFCCs, and adaptive preprocessing techniques. Enhanced model accuracy by fine-tuning self-supervised embeddings and applying SpecAugment, noise reduction, and real-world dataset adaptations.