Machine Learning Engineer - Ads Retrieval

reddit; London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Reddit seeks a Machine Learning Engineer in Ads Retrieval to enhance ad targeting through innovative ML solutions. Responsibilities include developing candidate sourcing algorithms and collaborating on large-scale data systems. This role requires strong experience in machine learning and programming, providing a chance to impact ad delivery at scale.

Benefits

Pension Scheme

Private Medical and Dental Scheme

Life Assurance, Income Protection

Workspace benefit for your home office

Personal & Professional development funds

Family Planning Support

Commuter Benefits

Flexible Vacation & Reddit Global Days Off

Qualifications

• 3+ years of experience with applied machine learning models.
• End-to-end experience in training and deploying ML models.
• Prior experience with information retrieval and recommendation systems.

Responsibilities

• Building and implementing ads retrieval and ML ranking systems.
• Researching and launching new model architectures for ads.
• Collaborating with stakeholders across various departments.

Skills

Machine Learning

TensorFlow

PyTorch

Statistical Analysis

Tools

Java

Python

Golang

C++

Job description

Social network you want to login/join with:

Machine Learning Engineer - Ads Retrieval, London

Client:

reddit

Location:

London, United Kingdom

Job Category:

Other

-

EU work permit required:

Yes

Job Reference:

1f8df558ea1d

Job Views:

25

Posted:

22.06.2025

Expiry Date:

06.08.2025

Job Description:

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 ,+ active communities and approximately M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit .

Ads Retrieval team’s mission is to identify business opportunities and provide ML models and data-driven solutions for candidate sourcing, recommendation, early ranking, and filtering in Ads upper funnel. The team works on:

• Build and iterate on candidate sourcing and early ranking Machine Learning models and algorithms to find the most relevant, engaging, and diversified ad candidates for global optimization and various product use cases.
• Design and establish a large-scale candidate indexing system to enable efficient candidate retrieval at a scale of millions to billions, powering ads recommendation and ranking with a good balance between quality and computation efficiency.

As a machine learning engineer in the ads retrieval team, you will research, formulate, and execute our mission to build end-to-end ML solutions and deliver the right ad to the right user under the right context with data and ML-driven solutions.

Your Responsibilities:

• Building ads retrieval and early ranking systems for critical ML tasks using advanced industrial-level techniques.
• Research, implement, test, and launch new model architectures including information retrieval, ANN, recommendation systems, and deep neural networks within high-dimensional information systems.
• Work on large-scale data systems, backend services, and product integration.
• Collaborate closely with multiple stakeholders across product, engineering, research, and marketing.

Who You Might Be:

• + years of experience with applied machine learning models using TensorFlow/PyTorch with large-scale ML systems.
• + years of end-to-end experience in training, evaluating, testing, and deploying machine learning models.
• Proficiency with programming languages (Java, Python, Golang, C++, or similar) and statistical analysis.
• Experience orchestrating complex data pipelines and system engineering on large-scale datasets.
• Prior experience with information retrieval and recommendation systems.
• Ads domain knowledge on product and ML solutions is a plus.

Benefits:

• Pension Scheme
• Private Medical and Dental Scheme
• Life Assurance, Income Protection
• Workspace benefit for your home office
• Personal & Professional development funds
• Family Planning Support
• Commuter Benefits
• Flexible Vacation & Reddit Global Days Off

Join us at Reddit, and help us build a community that is inclusive and empowering for everyone.