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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 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. 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. 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. What You’ll Do 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. What You Bring 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 Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a 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 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 In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.