We’re looking for a Machine Learning Engineer to join our tech team and help build the future of neuro-contextual advertising at global scale.
Who We Are
At 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.
Your Challenge
As a Machine Learning Engineer on Seedtag's Ad Exchange team, you will:
Build cutting‑edge AI to optimise revenue flow while ensuring the needs of publishers and advertisers are met.
Research, design, test, deploy, and maintain AI models in a fully online environment to maximise margins, reduce operational costs, and enhance Seedtag's targeting capabilities.
Design and implement classical ML algorithms and control systems to ensure delivery of internal campaigns and maximise monetisation outcomes.
Build end‑to‑end data pipelines to train, validate, and analyse production model behaviour through custom dashboards.
Continuously improve our MLOps infrastructure, CI/CD pipelines, internal automations, and AI‑supported workflows.
Collaborate closely with Data, Platform, and Backend Engineers to build services and infrastructure, from dataset generation to live model validation.
Tech Stack
We 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.
Python & Go microservices
Kafka, Kinesis, Redis, GCS
Kubernetes on GCP & AWS
Druid, MongoDB, scalable data lake architecture
Typescript (Node.js) and Scala across other parts of the company
What You’ll Need To Succeed
2–4 years of experience building and deploying ML systems in production.
Strong Python skills and solid software engineering fundamentals (APIs, async programming, testing, clean architecture).
Experience working on both model development and production deployment.
Understanding of distributed systems, microservices, and cloud‑native environments.
Familiarity with MLOps practices: model versioning, monitoring, CI/CD, reproducibility.
Experience with NLP, embeddings, and/or ranking models is a plus.
Comfortable debugging across layers: model behaviour, data issues, API performance, infrastructure bottlenecks.
Strong ownership mindset and ability to operate autonomously in fast‑moving environments.
Why Join Seedtag?
A key moment of growth with real ownership and global impact.
Flexible work model with 100% remote or hybrid options. (Remote contracts available in Spain, Italy, the UK, Belgium, the Netherlands, and Germany.)
Continuous learning through a learning platform and optional language classes.
A supportive, trust‑based culture that values well‑being.
Team activities, offsites, and opportunities to connect beyond work.
Additional Perks
Home office setup budget up to €1,000
Paid trips to our HQ in Madrid
MacBook Pro M3
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