Machine Learning Engineer

Overview

We are the platform turning browsing into shopping . We connect 200 million shoppers with deals they love while boosting local sales for hundreds of top retailers and brands.

We help consumers save time and money while making smart shopping decisions, and we support retailers and brands in engaging customers from online research to in-store purchases.

Ready to spark your growth with us?

Responsibilities

Your main responsibilities are linked to: Information Extraction and Enrichment from unstructured content, Data Platform activities (e.g., ETLs, ELTs), Multi Modal Extreme classification, Semantic Similarity in a Multi Modal setting and Recommendation systems. Here some examples:

• Autonomy to work on data pipelines, writing SQL queries; processing data using Pandas, Polars or Spark. Following good MLOps practices to develop and implement AI models in production environments, serving +100k predictions per day;
• Design a novel solution, from the problem to the final deployment stage; Develop AI models to process organic unstructured content such as offer images or text to extract valuable data for our users or clients;
• Manage, work on and improve the extensive Python codebases, following the company’s internal code style and guidelines;
• Keep up with the pace in the AI space! We tackle hard problems, we make tangible impact, so every advancement in the field, whether it is a new architecture or an off-the-shelf open source model, can bring us and our clients a ton of value! We value knowledge and curiosity, a lot.

Qualifications

• Coding: proficient Python knowledge; proven experience with PyTorch, Pandas, FastAPI/Flask, HuggingFace models ecosystem. Software Engineering skills are as important as the AI-related ones;
• MLOps: fully autonomous in building the pipelines (data, modelling, deployment) to bring the AI solutions from experiments to production;
• NLP and GenerativeAI: advanced knowledge of neural network architectures such as Transformers, GPT and proven experience in developing projects in this area (text classification, Named entity recognition, caption generation, unstructured data extraction, etc);
• Image and content: solid knowledge of neural architectures in the ComputerVision field, such as YOLO; Multi Modal Language Models or Vision Language Models; proven experience on developing projects in this area (image classification, image-text search, image understanding, image captioning, etc)
• Search: OpenSearch or ElasticSearch knowledge is a nice to have;
• Recommending Systems: good to have some proven experience (previous projects, academic works..) in building recommendation engines such as collaborative, content-based, knowledge based filtering based on custom deeplearning models or available libraries like Surprise, LightFM, Implicit etc.

Location

We have offices in Milan, Naples, Bologna and Cagliari but you can take advantage of our flexible hybrid mode or decide to work full-remote from anywhere in Italy.