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Machine Learning Systems Engineer, Ads ML Platform

Netherlands🌐 Remote💼 Full-time🗓 2026-06-23 → 2026-07-19

Core

Building scalable data infrastructure and feature management platforms to support high-quality training datasets and ML workflows for the Ads ML platform.

Role type

Senior IC machine learning systems engineer (data infrastructure)

Builds

Batch and real-time feature management platforms, training set generation systems, and agentic ML workflows for feature lifecycle management.

Domain

Internet / Advertising / Machine Learning Infrastructure

Deliverable

production ML models

Required skills

Distributed data systems (Spark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery), data pipeline engineering, API development, workflow orchestration, observability, performance tuning, reliability engineering, cost optimization, agentic workflow design, feature governance (lineage, validation, drift detection, versioning)

Preferred skills

Intelligent automation for ML systems, MLOps workflows spanning feature engineering to online serving

Technologies

Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery

Responsibilities

Design and build data infrastructure for large-scale feature and training set computation; Develop frameworks for batch and real-time features; Build platform capabilities for feature governance; Partner with ML engineers to integrate feature engineering workflows; Build systems supporting agentic ML workflows; Contribute to operational excellence through observability and cost optimization.

Rewrite
## Responsibilities - Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage. - Develop frameworks for batch and real-time features with a 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 initiatives. ## Requirements - 3+ years in data infrastructure/platform engineering or ML infrastructure platforms. - Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools. - Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies. - Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving. - Strong coding skills and ability to write clean, maintainable, well-tested code. ## Nice to Have - Experience building intelligent automation or agentic workflows for ML systems. - Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving. ## Benefits - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support. - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Private Pension plan with Employer-matching - 100% employer-sponsored group medical plan - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com. Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. Team Overview We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management. This is not a pure ML modeling role. The ideal candidate is excited about building reliable infrastructure, data pipelines, and developer-facing tools that make ML engineers more productive.
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