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Staff Machine Learning Engineer, ML Efficiency

Reddit

LocationUnited Kingdom, Netherlands
Senioritysenior
CompanyReddit
Recently checkedSep 8
Compensation

Salary not listed

Salary details are shown when available from the source listing. Sign in before applying so the role can be reviewed against your resume, salary goals, seniority, timezone, and location eligibility.

Requirements and working style

Decision details from the source listing

Experience

5+ years stated

Education

BS in Computer Science or related field, MS in Computer Science or related field, PhD in Computer Science or related field

Schedule

flexible

Benefits stated
Global benefit programsFamily planning supportGender-affirming careMental health and coaching benefitsGroup personal pension with employer matchPrivate medical and dental schemeIncome replacement programsBike to work schemeFlexible vacation and paid volunteer time offGenerous paid parental leave

These fields are normalized from the employer's text. Confirm details on the employer site before applying.

WFH.team analysis

What this posting tells you

Staff Machine Learning Engineer role at Reddit focusing on ML Efficiency. Remote work allowed within UK or Netherlands. Requires 5+ years software engineering experience, strong proficiency in Python, and experience with distributed systems and ML infrastructure. Flexible scheduling with comprehensive benefits. No salary provided.

Role lane

Backend, Customer success, Data, DevOps, Healthcare admin, HR and recruiting, Legal, Marketing, Operations, Patient support, Product, Security, Software

Where you can work

United Kingdom, Netherlands

Working hours

Europe/London, Europe/Amsterdam

Arrangement

senior · contract

Required signals
PythonGoC++RustJavadistributed systemsmachine learning infrastructureperformance engineeringdebuggingprofiling
Preferred signals
large-scale recommendation systemsranking systemsgenerative AIfoundation modelsPyTorch DistributedRayTensorFlowSparkGPU architecturescloud infrastructure cost optimizationreal-time ML inference applications
Confirm before applying
  • Compensation is not listed
Market context

Backend hiring on WFH.team

5,700active related roles
2,379new in the latest period
267.7jobs per 100 candidates
$202kmedian of comparable listed ranges

Category counts come from WFH.team's latest published remote job market snapshot.

Explore the remote job market
Skills and signals
PythonGoC++RustJavadistributed systemsmachine learning infrastructureperformance engineeringdebuggingprofilinglarge-scale recommendation systemsranking systemsgenerative AIfoundation modelsPyTorch DistributedRayRemote within the United Kingdom or the Netherlands
Job description

Staff Machine Learning Engineer, ML Efficiency at Reddit

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.

About the Team

The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem.

Responsibilities

  • Design and build systems that improve the efficiency of ML training and inference workloads.
  • Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
  • Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
  • Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
  • Build benchmarking frameworks and performance dashboards for training and serving systems.
  • Optimize distributed training infrastructure, data pipelines, and model serving architectures.
  • Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
  • Drive technical strategy for ML platform scalability, reliability, and cost efficiency.

Qualifications

Required

  • BS, MS, or PhD in Computer Science or a related field.
  • 5+ years of software engineering experience.
  • Strong proficiency in Python
  • Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
  • Experience building distributed systems at scale.
  • Experience with machine learning infrastructure, training systems, or model serving platforms.
  • Deep understanding of performance engineering and systems optimization.
  • Strong debugging and profiling skills.

Preferred

  • Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
  • Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
  • Familiarity with GPU architectures and performance analysis tools.
  • Experience optimizing cloud infrastructure costs across large ML workloads.
  • Contributions to internal platforms used by multiple ML teams.
  • Experience with building real time ML inference applications

What Success Looks Like

  • ML engineers can move from idea to experiment faster.
  • Training and inference costs decrease, performance increases, while model quality is maintained or improved.
  • GPU utilization and cluster efficiency increase.
  • Platform reliability improves as ML workloads scale.
  • Teams spend less time managing infrastructure and more time building models.
  • Average recommendation model size increases.

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 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.

Company context

Working remotely at Reddit

"The front page of the internet,” Reddit brings over 430 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities.

Team size
501-1000
Founded
2005
Application process

Review current openings on Reddit's official careers page before applying.

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