a
alii_shahzad

Ali S

@alii_shahzad

Software Engineer

Paquistão
Inglês, Urdu
Algumas informações são exibidas no idioma inglês.
Sobre mim
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.... Saiba mais

Habilidades

a
alii_shahzad
Ali S
offline • 
Tempo médio de resposta: 75 horas

Conheça meus serviços

Integrações de IA
I will build autonomous multi agent systems using langgraph, langchain
A partir deUS$ 90 /projetoMais detalhes
Automações e Agentes
I will develop ai voice agents with vapi, livekit, fastapi
A partir deUS$ 50 /projetoMais detalhes

Portfólio

Experiência profissional

Software Engineer

APIMatic.io • Período integral

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 • Período integral

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 • Meio período

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.