PpWe’re looking for a Machine Learning Engineer to join our tech team and help build the future of neuro-contextual advertising at global scale. /p h3Who We Are /h3 pAt Seedtag, our mission is to transform advertising by proving that effectiveness and user privacy can truly coexist. As the leading Neuro-Contextual Advertising Company, we combine Artificial Intelligence, Natural Language Processing, Computer Vision, and neuroscience to understand not only what content is about, but how it makes people feel and what they intend to do next. Our proprietary AI, Liz, enables brands to connect with audiences across the open web and Connected TV without cookies or user tracking. Founded in 2014 by two ex-Googlers, Seedtag has grown to 700+ Seedtaggers in 17 countries, backed by €250M in funding, and operates today as a global ad-tech leader. /p h3Your Challenge /h3 pAs a Machine Learning Engineer on Seedtag's Ad Exchange team, you will: /p ul liBuild cutting‑edge AI to optimise revenue flow while ensuring the needs of publishers and advertisers are met. /li liResearch, design, test, deploy, and maintain AI models in a fully online environment to maximise margins, reduce operational costs, and enhance Seedtag's targeting capabilities. /li liDesign and implement classical ML algorithms and control systems to ensure delivery of internal campaigns and maximise monetisation outcomes. /li liBuild end‑to‑end data pipelines to train, validate, and analyse production model behaviour through custom dashboards. /li liContinuously improve our MLOps infrastructure, CI/CD pipelines, internal automations, and AI‑supported workflows. /li liCollaborate closely with Data, Platform, and Backend Engineers to build services and infrastructure, from dataset generation to live model validation. /li /ul h3Tech Stack /h3 pWe operate at a large scale, supporting up to 120k requests per second, with ML models responding in under 10 milliseconds and processing 20 TB of data daily. /p ul liPython Go microservices /li liKafka, Kinesis, Redis, GCS /li liKubernetes on GCP AWS /li liDruid, MongoDB, scalable data lake architecture /li liTypescript (Node.js) and Scala across other parts of the company /li /ul h3What You’ll Need To Succeed /h3 ul li2–4 years of experience building and deploying ML systems in production. /li liStrong Python skills and solid software engineering fundamentals (APIs, async programming, testing, clean architecture). /li liExperience working on both model development and production deployment. /li liUnderstanding of distributed systems, microservices, and cloud‑native environments. /li liFamiliarity with MLOps practices: model versioning, monitoring, CI/CD, reproducibility. /li liExperience with NLP, embeddings, and/or ranking models is a plus. /li liComfortable debugging across layers: model behaviour, data issues, API performance, infrastructure bottlenecks. /li liStrong ownership mindset and ability to operate autonomously in fast‑moving environments. /li /ul h3Why Join Seedtag? /h3 ul liA key moment of growth with real ownership and global impact. /li liFlexible work model with 100% remote or hybrid options. (Remote contracts available in Spain, Italy, the UK, Belgium, the Netherlands, and Germany.) /li liContinuous learning through a learning platform and optional language classes. /li liA supportive, trust‑based culture that values well‑being. /li liTeam activities, offsites, and opportunities to connect beyond work. /li /ul h3Additional Perks /h3 ul liHome office setup budget up to €1,000 /li liPaid trips to our HQ in Madrid /li liMacBook Pro M3 /li /ul /p #J-18808-Ljbffr