JOB DESCRIPTION
As an ML Engineer, you´ll join our Data Science team, distributed across Paris, Lyon, Barcelona, and Brussels.
The team focuses on implementing, maintaining, and continuously improving our recommender systems.
Today, we deliver personalized sales recommendations to millions of users in real time-and we´re now scaling to include hundreds of thousands of products.
You will bridge Data Science and Engineering to build, deploy, and maintain real-time recommendation models at scale.
You´ll design robust model-serving architectures and ensure reliable, low-latency predictions for millions of users.
Responsibilities:
- Build and maintain high-performance APIs and microservices for real-time model serving.
- Implement scalable MLOps pipelines for model versioning, deployment, and monitoring.
- Collaborate with Data Scientists to productionize models and integrate them into business workflows.
- Develop automated monitoring and alerting for model performance and data drift.
- Continuously improve infrastructure scalability and reliability on Kubernetes and cloud environments.
Requirements:
- At least 5 years of experience in software or ML engineering.
- Strong programming skills in Java and Python; solid understanding of SQL.
- Scala knowledge is a plus.
- Experience with MLOps tools (MLflow, Kubeflow, Airflow, or similar).
- Familiarity with streaming or batch frameworks (Beam, Flink, Spark, Kafka).
- Cloud experience (GCP, AWS, or Azure) and container orchestration (Kubernetes).
- Excellent written and spoken English communication.
BENEFITS
- Be part of a dynamic and international team!
- Flexible schedule
- Team buildings & afterworks
RECRUITMENT PROCESS
- 1 HR Interview
- 2 Technical Interview
- 3 Team ITW
All our positions are open to people with health conditions or impairments.
We are convinced that it is up to you to define the way you work, to develop yourself and to progress. At Veepee we guarantee that you can just be yourself! For the service of diversity and inclusion, Veepee is committed to reviewing all applications received on an equal basis.
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