This role sits at the core of a next-generation ecommerce search and discovery platform that operates at massive general scale. You will be responsible for building and optimizing machine learning systems that directly impact relevance, recall, and business-critical outcomes such as conversion and revenue. The environment is highly technical and innovation-driven, with a strong emphasis on production-grade ML systems and measurable impact.

You will collaborate with engineers across distributed teams to push the boundaries of LLMs, deep learning, and large-scale data systems. Design, build, and deploy robust machine learning systems for search and discovery, including NLP, image-based, and multimodal models that improve recall and relevance. Develop and optimize ML/DL models using transformer architectures and LLM techniques to enhance system performance and business KPIs.

Translate research ideas and hypotheses into production-ready engineering solutions that improve search quality, ranking, and user experience. Work on large-scale distributed data pipelines and ML workflows using big data technologies to support end-to-end model development and deployment. Collaborate closely with cross-functional engineering teams to integrate models into broader platforms and ensure system scalability and reliability.





Conduct performance optimization and iterative experimentation to continuously improve model efficiency and business impact. 3+ years of professional experience in applied machine learning with a proven track record of delivering production-grade ML systems. ~ Strong expertise in NLP, particularly transformer-based models, along with solid understanding of classical machine learning techniques. ~ Advanced Python skills and hands-on experience with deep learning frameworks (PyTorch preferred). ~ Strong experience with SQL (e.g., SparkSQL, MySQL or similar) and working knowledge of large-scale data processing systems such as PySpark. ~ Ability to translate business problems into data-driven hypotheses and implement scalable engineering solutions with measurable impact. ~ Nice to have: experience with A/B testing, cloud platforms (AWS/GCP/Azure), Rust or C/C++, strong algorithmic thinking, and interest in performance optimization. Fully remote work setup, allowing you to choose your location. Home office stipend to support your remote work environment.

Annual learning and development budget for continuous professional growth. Opportunity to work with highly skilled peers on impactful, large-scale AI systems. 80,000 - $120,000 USD depending on experience and performance. #

📌 Senior Machine Learning Engineering (Madrid)
🏢 Jobgether
📍 Madrid