Job Overview
Location
Remote - United Kingdom
Job Type
Full-time
Category
Software Engineering
Date Posted
July 6, 2026
Full Job Description
đź“‹ Description
- • Design and build scalable data infrastructure to support large-scale feature and training set computation, transformation, and storage for Reddit’s Ads ML Platform.
- • Develop batch and real-time feature frameworks with a focus on reliability, scalability, and ease of use for ML engineers.
- • Build platform capabilities for feature governance including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning.
- • Partner closely with ML engineers to integrate feature engineering workflows seamlessly into ML production systems.
- • Design and implement agentic and automated ML workflows for feature discovery, quality evaluation, and end-to-end feature lifecycle management.
- • Contribute to operational excellence by enhancing observability, tuning system performance, improving reliability, and optimizing infrastructure costs.
- • Create developer-facing tools and APIs that empower ML teams to efficiently generate, manage, and consume high-quality features.
- • Ensure data pipelines and systems are robust, maintainable, and capable of handling Reddit’s high-volume, real-time user data at scale.
- • Collaborate across teams to standardize feature definitions and improve consistency across ML models used in advertising systems.
- • Support the evolution of the training dataset generation platform to enable faster experimentation and model iteration.
- • Implement monitoring and alerting systems to detect data quality issues and system failures in real-time.
- • Optimize compute and storage resources to reduce latency and cost while maintaining high throughput for feature serving.
- • Document system architecture, data flows, and operational procedures to ensure knowledge sharing and team scalability.
- • Stay current with advancements in MLOps, feature stores, and distributed data systems to continuously improve platform capabilities.
🎯 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.
- • Experience building intelligent automation or agentic workflows for ML systems is a strong plus.
🏖️ 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.
- • Group Personal Pension Scheme with Employer match.
- • Private Medical and Dental Scheme.
- • Income Replacement Programs.
- • Bike to Work scheme.
- • Flexible Vacation & Paid Volunteer Time Off.
- • Generous Paid Parental Leave.
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Reddit Inc.
Reddit is a social media platform where users submit, vote, and comment on content organized into topic-based communities called subreddits. Founded in 2005, it offers forums for news, hobbies, advice, and discussion, enabling real-time conversations and content ranking through upvotes and downvotes. With millions of daily active users globally, Reddit hosts diverse communities moderated by volunteers, supports multimedia posts, and provides advertising and premium membership options. The platform emphasizes user anonymity, community governance, and crowdsourced information, making it a hub for niche interests, viral content, and public discourse. Reddit went public in 2024 and is headquartered in San Francisco.
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