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Amsterdam
1 day ago
Machine Learning Systems Engineer, Ads ML Platform logo

Machine Learning Systems Engineer, Ads ML Platform

Reddit, Inc.

Amsterdam
1 day ago
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Machine Learning Systems Engineer, Ads ML Platform

Reddit is hiring a Machine Learning Systems Engineer for its Ads ML Platform team. The role involves building scalable data infrastructure and developer tools for feature management, not pure ML modeling. Requires 3+ years in data infrastructure/platform engineering and experience with distributed systems like Spark, Kafka, or Kubernetes.

AIRemoteFull-timeMid LevelApache SparkPySpark

Machine Learning Systems Engineer, Ads ML Platform

Reddit is hiring a Machine Learning Systems Engineer for its Ads ML Platform team. The role involves building scalable data infrastructure and developer tools for feature management, not pure ML modeling. Requires 3+ years in data infrastructure/platform engineering and experience with distributed systems like Spark, Kafka, or Kubernetes.

Apply
AIRemoteFull-timeMid LevelApache Spark

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Remote

Experience Required

3 years

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)
Apache SparkPySparkApache FlinkApache KafkaRayApache AirflowKubernetesBigQueryMachine LearningMLOpsData PipelinesAPIsWorkflow SystemsDeveloper ToolsFeature Engineering

Preferred Qualifications

Technical (Nice-to-have)
Intelligent AutomationAgentic WorkflowsML InfrastructureModel DeploymentOnline Serving

Key Responsibilities

  • •Design and build data infrastructure for large-scale feature and training set computation, transformation, and storage.
  • •Develop frameworks for batch and real-time features with focus on reliability, scalability, and ease of use.
  • •Build platform capabilities for feature governance including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning.
  • •Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.
  • •Build systems that support agentic ML workflows including automated feature discovery, feature quality evaluation, and feature lifecycle management.
  • •Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization.
Machine LearningData InfrastructureAds ML PlatformRemoteNetherlandsUKSparkKafkaKubernetesMLOps
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