f
farazabir

Faraz Ahmed

@farazabir
Bangladesh
Inglés
Parte de la información aparece en idioma inglés.
Sobre mí
Hello, I’m Faraz Ahmed Abir, a Computer Science student and professional developer specializing in machine learning, AI, and modern application development. I work with startups and individuals to build scalable, real-world digital solutions, with a focus on cross-platform mobile apps and high-performance web interfaces. My expertise includes Python, Node.js, React, and Java, enabling me to deliver reliable backend systems and intuitive user experiences. I’m passionate about turning ideas into practical, impactful products through clean architecture and smart technology.... Lee más

Habilidades

f
farazabir
Faraz Ahmed
desconectado • 

Revisa mis servicios

Integraciones de IA
I will create custom ai apps using openai gpt4, langchain, hugging face more
DeUSD 395 / proyectoMás información
Aplicaciones móviles de IA
I will develop ai mobile app and web app custom ai models chatbots gpt with automation
DeUSD 100 / proyectoMás información

Porfolio

Experiencia laboral

Software Developer

Drag me • Tiempo completo

Sep 2023 - Present • 2 yrs 8 mos

Technologies: React Native, Expo, Node.js, Spring Boot, Django, AWS (ECS, ECR, S3, Lambda), RabbitMQ, PostgreSQL, Docker. Developed and deployed a cross-platform mobile app, boosting user engagement by 40%. Streamlined project workflows, enhancing overall efficiency by 25%. Designed and scaled a microservices architecture, improving system performance 3x. Automated event submissions with a Slack bot, reducing manual effort by 70%. Led a team of 2 developers and 1 data engineer, improving workflow efficiency by 40%. Developed eCommerce and chat microservices, increasing user interaction by 60%. Implemented a video-sharing feature using AWS S3, Spring Boot, RabbitMQ, and FFmpeg.

Software Developer

LinguaVid – AI-Powered Video Translation & Voice Cloning • Freelance

May 2025 - Jul 2025 • 2 mos

Technologies: Python, FastAPI, Django, Next.js, Whisper Model, FFmpeg, Docker, RabbitMQ Built an AI-driven pipeline for speech extraction, translation, and synthesis, reducing processing time by 45%. Integrated Whisper Speech model, Google Text-to-Speech, and FFmpeg for high-quality speech-to-text and voice cloning. Deployed scalable microservices with Docker, Django, and FastAPI, enabling low-latency video translation.