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Machine Learning Systems Engineer, Ads ML Platform

Reddit Remote - United Kingdom 2mo ago
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About Reddit (Wikipedia Record):

Reddit is an American social news website, news aggregator, forum and social media platform. Registered users submit content to the site such as links, text posts, images, and videos, which are then voted up or down by other members. Posts are organized by subject into user-created boards called "subreddits". Submissions with more upvotes appear towards the top of their subreddit and, if they receive enough upvotes, ultimately on the site's front page. Reddit administrators moderate the communities. Moderation is also conducted by subreddit-specific moderators, who are unpaid volunteers. It is operated by Reddit, Inc., based in San Francisco.

About the Role

<div class="content-intro"><div class="c-message_kit__blocks c-message_kit__blocks--rich_text"> <div class="c-message__message_blocks c-message__message_blocks--rich_text" data-qa="message-text"> <div class="p-block_kit_renderer" data-qa="block-kit-renderer"> <div class="p-block_kit_renderer__block_wrapper p-block_kit_renderer__block_wrapper--first"> <div class="p-rich_text_block"> <div class="p-rich_text_section">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 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit <a class="c-link" href="http://www.redditinc.com/" target="_blank" data-stringify-link="http://redditinc.com" data-sk="tooltip_parent">www.redditinc.com</a>.</div> </div> </div> </div> </div> </div></div><p><strong>Location:&nbsp;</strong>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.</p> <p><strong>Team Overview</strong></p> <p>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 &amp; realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management.</p> <p>We are looking for an engineer with experience in building high-scale data infrastructure and exposure to ML platforms to help evolve and scale our feature management systems.</p> <p>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.</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage.</li> <li>Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use.</li> <li>Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning</li> <li>Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.</li> <li>Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management</li> <li>Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives.</li> </ul> <p><strong>What You Bring</strong></p> <ul> <li>3+ years in data infrastructure/platform engineering or ML infrastructure platforms.</li> <li>Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools.</li> <li>Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies.</li> <li>Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training, experimentation, or online serving.</li> <li>Strong coding skills and ability to write clean, maintainable, well-tested code.</li> <li>Experience building intelligent automation or agentic workflows for ML systems is a strong plus</li> <li>Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a plus</li> </ul> <p><strong>Benefits:</strong></p> <ul> <li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li> <li>Family Planning Support</li> <li>Gender-Affirming Care</li> <li>Mental Health &amp; Coaching Benefits</li> <li>Group Personal Pension Scheme with Employer match</li> <li>Private Medical and Dental Scheme<

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