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Remote ML Infrastructure Engineer - Ads Platform

Reddit Inc.
Greater London, UK
9 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source
www.collegerecruiter.com

Tech stack

Application Programming Interfaces (APIs) Airflow Big Data Data Infrastructure Data Systems Programming Tools Apache Spark Kubernetes Machine Learning Operations Data Pipelines

Job description

Reddit, Inc. is seeking a data infrastructure engineer to design scalable data systems and ML feature platforms. You will build production services, data pipelines, APIs, and developer tools to empower ML engineers and data scientists.

We expect 3+ years in data infrastructure with hands-on experience in Spark, Airflow, Kubernetes, and big data stacks. This is a remote-friendly role open to the UK and Netherlands, focused on reliability, performance, and developer productivity.

Requirements

We expect 3+ years in data infrastructure with hands-on experience in Spark, Airflow, Kubernetes, and big data stacks. This is a remote-friendly role open to the UK and Netherlands, focused on reliability, performance, and developer productivity. #J-18808-Ljbffr

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

Moments

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2:15 min

Empowering domain teams with an open data platform

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

2:14 min

Exploring internal AI product initiatives and global engineering roles

Maria Apazoglou · Coffee With Developers

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

2:28 min

Understanding Kubernetes architecture and core cluster components

Marc Nimmerrichter · World Congress 2022

3:05 min

Audience questions on AI agents and pipeline vectorization

Joy Joy · World Congress 2024

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

Videos

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29:05
World Congress 2026 Europe • about 2 months ago

Understanding Kubernetes in a visual way

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From Messy Queries to Scalable Systems - How Data Engineering actually works thumbnail
31:15
World Congress 2026 Europe • about 2 months ago

From Messy Queries to Scalable Systems - How Data Engineering actually works

Sandhya Menon

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35:19
Coffee With Developers • 4 months ago

Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps

Hazal Mestci, Raph Terrier

PySpark - Combining Machine Learning & Big Data thumbnail
43:26
LIVE • almost 6 years ago

PySpark - Combining Machine Learning & Big Data

Ayon Roy

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment thumbnail
25:41
World Congress 2024 • about 2 years ago

AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment

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