We are looking for a Machine Learning Engineer to join our engineering team and help us build intelligent, scalable, production-grade AI systems.

This is a hands-on engineering role for someone with a strong multi-disciplinary toolkit across computer vision, natural language processing, information retrieval, generative AI, and production MLOps.

🧩 What You Will Do

You will help design, build, and deploy AI-powered systems that improve product discovery, search relevance, recommendation quality, image understanding, and conversational user experiences across our marketplace.

Your work may include:

• Building image similarity, product matching, and visual search capabilities.

• Developing semantic search and dense retrieval systems.

• Designing and deploying LLM-powered experiences for intelligent search and conversational interfaces.

• Creating autonomous workflows and tool-use systems using agentic AI frameworks.

• Scaling asynchronous ML workloads and event-driven data pipelines.

• Deploying, monitoring, and optimizing production ML APIs in cloud environments.

✅ What We Are Looking For

• Strong software engineering fundamentals and ability to ship reliable production systems.

• A pragmatic engineer who can turn AI concepts into production-ready systems.

• Strong problem-solving ability and ownership mindset.

• Interest in e-commerce, marketplace platforms, search, discovery, and user experience.

• Ability to collaborate with engineering, product, and business teams.

• Curiosity, adaptability, and enthusiasm for building with emerging AI technologies.

As well as, experience in some or most of the following areas:

• Computer Vision & Image Similarity

  • Feature extraction, image embeddings, and high-dimensional similarity matching.

  • Deep metric learning and visual search systems.

  • OCR and text extraction from images.

• Advanced Information Retrieval

  • Dense retrieval, vector search, and semantic search optimization.

  • Experience with vector databases such as Pinecone, Milvus, or Qdrant.

  • Practical understanding of ranking, relevance, and retrieval evaluation.

• Generative AI & Large Language Models

  • Prompt engineering, fine-tuning, and deploying LLMs.

  • Experience building LLM-powered search, recommendation, or conversational interfaces.

  • Familiarity with Hugging Face models and modern NLP tooling.

• Agentic AI Frameworks

  • Building autonomous workflows and tool-use systems.

  • Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or CrewAI.

  • Designing reliable multi-step AI pipelines.

• Asynchronous Systems & Queuing

  • Experience with distributed task queues and message brokers.

  • Practical knowledge of systems such as RabbitMQ.

  • Building event-driven data pipelines and asynchronous ML workloads.

• Production MLOps

  • Deploying, monitoring, and scaling ML services in production.

  • Experience with AWS or GCP.

  • Working with Docker, Kubernetes, and low-latency ML APIs.

  • Understanding of model observability, performance monitoring, and reliability.

• Core Engineering

  • Strong programming skills in Python.

  • Solid knowledge of SQL.

  • Experience with ML frameworks such as PyTorch, TensorFlow, and Hugging Face.

🎁 What We Offer

• Hybrid working model

• Competitive compensation package

• The opportunity to work in a high-traffic environment (millions of users) where your code impacts the Greek e-commerce market daily.

• A modern, agile work environment (Tribes & Chapters).

• Access to training programs and skill-development tools