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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 AreAt 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.
If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you’ll feel right at home here.
Your ChallengeAs a Machine Learning Engineer on Seedtag's Ad Exchange team, you will:
We measure success by impact and value, not by volume of features or lines of code.
Failure Is Allowed, Learning Is a Must
Experimentation is key to innovation. We test early, iterate often, and learn fast.
We Are All Scouts
We take ownership and leave things better than we found them.
We Are Data-Driven
Data informs our decisions and helps us continuously improve our systems and results.
Tech StackWe 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.
Our Stack Includes
Send us your CV and let’s build the future of neuro-contextual advertising together.
Who We AreAt 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.
If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you’ll feel right at home here.
Your ChallengeAs 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.
We measure success by impact and value, not by volume of features or lines of code.
Failure Is Allowed, Learning Is a Must
Experimentation is key to innovation. We test early, iterate often, and learn fast.
We Are All Scouts
We take ownership and leave things better than we found them.
We Are Data-Driven
Data informs our decisions and helps us continuously improve our systems and results.
Tech StackWe 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.
Our Stack Includes
- 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
- 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.
- 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.
- Home office setup budget up to €1,000
- Paid trips to our HQ in Madrid
- MacBook Pro M3
Send us your CV and let’s build the future of neuro-contextual advertising together.
Key Skills
Ranked by relevance
ai
machine learning
mlops
cicd
natural language processing
artificial intelligence
computer vision
microservices
python
scala
redis
cloud
gcp
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- Posted
- Apr 08, 2026
- Type
- Other
- Level
- Not Applicable
- Location
- Hamburg
- Company
- Seedtag
Industries
Advertising Services
Categories
Engineering
Information Technology
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2026-04-08
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Intermediate Backend Software Developer
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