This paper addresses the challenge of efficient and accurate retrieval of Waste Electrical and Electronic Equipment (WEEE) products, specifically printer cartridges. Traditional recycling methods, heavily reliant on manual inspections, are labour-intensive and inefficient. To overcome these limitations, we propose a hybrid search and re-ranking approach which incorporates a combination of NLP-based methods. By leveraging these methods, we aim to improve the recall@1k performance of WEEE product retrieval, facilitating more efficient and sustainable WEEE recycling practices. The experimental results achieve a recall@1k score of 60.18%, showing the effectiveness of our approach. This improvement has significant implications for the recycling industry, enabling more accurate identification and sorting of WEEE products and ultimately contributing to a more sustainable circular economy.