Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Engineer - Ads Conversion Modeling

A Giants Early Learning Center
London
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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 82M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

As a company, Reddit primarily generates revenue through advertising, and we're working towards building a massive business to fund our mission. We distinguish ourselves from other digital ad platforms by attracting advertisers who want to connect with a specific target audience because of our passionate and engaged communities.

Find out if this opportunity is a good fit by reading all of the information that follows below.The Ads Conversions Modeling Team is entrusted with the development and maintenance of a diverse set of Machine Learning models that are responsible for predictions regarding user conversions after engaging with Reddit. The creation and enhancement of these models plays a crucial role in our organization's efforts to optimize advertising effectiveness and drive business growth. We are looking for a motivated engineer that will help us advance our vision. As a diverse group of software engineers, product managers, data scientists, and ads experts, we are excited for you to join our team!As a machine learning engineer in the Ads Conversion Modeling Team, you will research, formulate, and execute projects, and actively participate in the end-to-end implementation process. You will collaborate with cross-functional teams to ensure successful product delivery. You will also be able to contribute your expertise and shape the future of ads ML at Reddit!Your Responsibilities :Building industrial-level models for critical ML tasks with advanced modeling architectures and techniquesResearch, implement, test, and launch new model architectures including deep neural networks with advanced pooling and feature interaction architecturesSystematic feature engineering works to convert all kinds of raw data in Reddit (dense & sparse, behavior & content, etc) into features with various FE technologies such as aggregation, embedding, sub-models, etc.Contribute meaningfully to team strategy. We give everyone a seat at the table and encourage active participation in planning for the futureWho You Might Be:Tracking records of consistently driving KPI wins through systematic works around model architecture and feature engineering3+ years of experience with industry-level Machine Learning models3+ years of experience with mainstream ML frameworks (such as Tensorflow and Pytorch)3+ years of end-to-end experience of training, evaluating, testing, and deploying industry-level modelsDeep learning experience is a strong plusExperience in orchestrating complicated data generation pipelines on large-scale dataset is a plusExperience with Ads domain is a plusExperience with Recommendation Systems is a plusBenefits:Pension SchemePrivate Medical and Dental SchemeLife Assurance, Income ProtectionWorkspace benefit for your home officePersonal & Professional development fundsFamily Planning SupportCommuter BenefitsFlexible Vacation & Reddit Global Days OffJoin us at Reddit, and help us build a community that is inclusive and empowering for everyone.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 you need assistance or an accommodation due to a disability, please contact us at

.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.