Machine Learning Engineer
Seedtag
Ouderkerk aan de Amstel, Netherlands
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Remote
Ouderkerk aan de Amstel, Netherlands
Tech stack
Multitier Architecture
API
Artificial Intelligence
Amazon Web Services (AWS)
Application Performance Management
Cloud Computing
Computer Programming
Continuous Integration
Software Debugging
Distributed Systems
Python
Machine Learning
MongoDB
Node.js
Redis
Software Deployment
TypeScript
Model Validation
Backend
Data Lake
Kubernetes
Druid
Kafka
Machine Learning Operations
Software Version Control
Data Pipelines
Microservices
Job description
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., 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.
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
Requirements
- 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.
Benefits & conditions
-
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
About the company
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.
If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you'll feel right at home here.