Machine Learning Systems Engineer, Ads ML Platform in London

Machine Learning Systems Engineer, Ads ML Platform in London

London Full-Time 70000 - 90000 £ / year (est.) Working from home possible
NLP PEOPLE

At a Glance

  • Tasks: Design and build scalable data infrastructure for machine learning features and training datasets.
  • Company: Join Reddit, a vibrant community platform with a flexible remote work culture.
  • Benefits: Enjoy global benefits, mental health support, flexible vacation, and generous parental leave.
  • Other info: Be part of a diverse team committed to innovation and operational excellence.
  • Why this job: Make an impact by building reliable systems that empower ML engineers and enhance user experiences.
  • Qualifications: 3+ years in data infrastructure or ML platforms, strong coding skills, and experience with distributed systems.

The predicted salary is between 70000 - 90000 £ per year.

Reddit is a community of communities built on shared interests, passion, and trust. It is home to the most open and authentic conversations on the internet, with over 100,000 active communities and approximately 126 million daily active unique visitors.

Location: Reddit has a flexible first workforce. 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 & real-time feature management platform, training set generation platform, sequence features platform, 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.
  • 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.

In select roles and locations, the interviews will be recorded, transcribed, and summarised by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription, and summarisation prior to any scheduled interviews. During the interview, we will collect personal information to evaluate your application for employment or an independent contractor role. 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.

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.

Machine Learning Systems Engineer, Ads ML Platform in London employer: NLP PEOPLE

Reddit is an exceptional employer that fosters a flexible and inclusive work culture, allowing employees to work remotely from anywhere in the UK or the Netherlands. With a strong focus on professional development, Reddit offers comprehensive benefits including family planning support, mental health resources, and generous parental leave, ensuring that team members can thrive both personally and professionally. The opportunity to contribute to innovative projects in a collaborative environment makes Reddit a rewarding place for those passionate about building impactful technology.

NLP PEOPLE

Contact Details:

NLP PEOPLE Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Systems Engineer, Ads ML Platform in London

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We think you need these skills to ace Machine Learning Systems Engineer, Ads ML Platform in London

Data Infrastructure Engineering
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Spark

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