Systems Engineer
We usually respond within three days
The role
• Design and ship personalization and search/ranking systems (candidate generation, ranking and re-ranking).
• Build real-time feature pipelines and embeddings; maintain feature stores and user/item models.
• Develop online inference services with strict latency/availability SLOs and robust A/B experimentation.
• Define offline/online evaluation metrics (CTR/Conversion/NDCG, calibration, counterfactuals) and guardrails.
• Partner with Product, Data and Platform teams to instrument events and drive measurable impact.
What you bring
• MSc/BSc in Computer Science, Applied Mathematics, Statistics or similar.
• 5+ years in recommender systems, search or large-scale ML engineering.
• Strong Python and SQL; experience with PyTorch or TensorFlow for training and evaluation.
• Experience with streaming and near-real-time data (Kafka/Kinesis, Spark/Flink) and low-latency serving.
• Exposure to feature stores, embeddings, vector retrieval (pgvector, Pinecone, Weaviate).
• Solid understanding of evaluation design, experiment analysis and metrics trade-offs.
• Professional English; Swedish or Finnish is a plus.
Nice to have
• Bandits/exploration, reinforcement learning or knowledge-graph-based recommenders.
• Privacy, fairness and bias mitigation techniques in personalization.
• End-to-end product experience (journeys, notifications, search, feed).
• Cost optimization and caching strategies at scale.
- Department
- Information Technology
- Locations
- Sweden, Finland
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