Summary
✨ AI‑Generated
A full-time on-site AI engineering role focused on designing, developing, and deploying intelligent solutions for a scalable multi-vendor commerce environment. You will apply AI and software engineering capabilities to improve marketplace operations, user experiences, analytics, and business efficiency.
Highlights
Full-time on-site AI engineering opportunity in a modern e-commerce environment. The role focuses on designing, developing, and deploying AI-driven solutions within a scalable marketplace platform serving businesses of different sizes.
Description
the job
Company Description CartBuzz is a modern multi-vendor e-commerce platform designed to help businesses launch, manage, and scale online stores efficiently.
The platform connects sellers, customers, and technology in a unified ecosystem that supports product management, secure payments, customizable storefronts, vendor dashboards, advanced analytics, and automated marketplace operations.
With a strong emphasis on speed, reliability, and a clean user experience, CartBuzz enables vendors to expand their reach and grow revenue.
By combining innovative software development with scalable marketplace infrastructure, the company serves startups, small businesses, and large enterprises alike.
CartBuzz is focused on shaping the future of online commerce with intelligent, fast, and flexible marketplace
technology.
Role Description This is a full-time, on-site Al Engineer
role based in Amman, Jordan.
The Al Engineer will design, develop, and deploy Al-driven solutions that enhance CartBuzz's e-commerce platform, including recommendation systems, search optimization, and intelligent seller and buyer experiences.
Responsibilities include building and training machine learning and deep learning models, integrating them into production systems, and collaborating with software engineers and product teams to deliver scalable, high-performance features.
The role involves conducting experiments, evaluating models using appropriate metrics, and iterating based on real-world data and feedback.
The Al Engineer will also contribute to code reviews, documentation, and best practices for Al and data-driven development.
Qualifications
Strong foundation in Computer Science and Software Development, with experience building and deploying production-grade applications.
Hands-on experience with Machine Learning and Deep Learning, including model training, fine-tuning, evaluation, and optimization.
Practical experience with Natural Language Processing (NLP) and Large Language Models (LLMs), including conversational Al, Retrieval-Augmented Generation (RAG), and chatbot development.
• Experience working with multimodal models, such as Image-to-Text and Text-to-Image systems, is highly desirable.
Proficiency in Python and experience with Al frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Familiarity with frameworks and tools such as LangChain, Llamalndex, embeddings, and vector databases (Qdrant, Pinecone, Weaviate, or similar) is a
plus.
• Experience building APIs and model-serving solutions using FastAPI or similar technologies.
• Experience working with cloud and containerized environments (GCP, AWS, Docker, Kubernetes) is beneficial.
Bachelor's degree or higher in Computer Science, Engineering, or a related technical field, with 2+ years of relevant Al or ML engineering experience.
Strong analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams.
