LoopMe
Technology
DataScientist/MachineLearningEngineer-AIatMassiveScale
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Scientist / Machine Learning Engineer - AI at Massive Scale at LoopMe. Skills: Machine learning, Data pipelines, Python development. Design large-scale ML pipelines. Build large-scale ML pipelines”
What You'll Achieve.
Measurable impact
Industry & Context.
Real-world problems
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Maths, Engineering, Physics or similar, 3+ years commercial Python experience, Track record building ML pipelines that handle large-scale data, Excellent communication skills, Curious, scientific mindset
Nice to Have
MSc/PhD a plus, Experience with adtech or real-time bidding, Agile / Scrum experience, Knowledge of high-availability infrastructure, Airflow expertise
What You'll Do.
Design large-scale ML pipelines
Build large-scale ML pipelines
Run large-scale ML pipelines
Process terabytes of data
Apply supervised learning
Apply custom algorithms
Apply statistical modelling
Ship production-grade Python code
Partner with engineering
Take models from idea to production
Take models to impact
How You'll Work.
Team & Collaboration
Agile squads; DS peers; ML peers; Engineering peers; Product teams; Engineering teams
Communication Scope
Working across time zones
Process & Methodology
Agile
Full Job Description
**Help us push AI further — and faster** LoopMe’s [Data Science team](https://www.glassdoor.com/Reviews/LoopMe-Data-Scientist-Reviews-EI_IE911164.0,6_KO7,21.htm) builds production AI that powers real-time decisions for campaigns seen by hundreds of millions of people every day. We process billions of data points daily — and we don’t just re-apply old tricks. We design and deploy genuinely novel machine learning systems, from idea to prototype to production. You’ll join a high-trust team that has a **5-star Glassdoor rating** led by [Leonard Newnham](https://www.linkedin.com/in/leonardnewnham/), where your work moves fast, ships to production, and makes measurable impact. **What you’ll do:** * Design, build, and run large-scale ML pipelines that process terabytes of data * Apply a mix of supervised learning, custom algorithms, and statistical modelling to real-world problems * Ship production-grade Python code that’s clear, documented, and tested * Work in small, agile squads (3–4 people) with DS, ML, and engineering peers * Partner with product and engineering to take models from idea → production → impact * Work with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse and more **What you bring:** * Bachelor’s degree in Computer Science, Maths, Engineering, Physics or similar (MSc/PhD a plus) * 3+ years’ commercial Python experience * Track record building ML pipelines that handle large-scale data * Excellent communication skills — comfortable working across time zones * A curious, scientific mindset — you ask “why?” and prove the answer **Bonus if you have:** * Experience with adtech or real-time bidding * Agile / Scrum experience * Knowledge of high-availability infrastructure (ElasticSearch, Kafka, ClickHouse) * Airflow expertise **About the Data Science Team:** We’re 17 ML engineers, data scientists, and data engineers, distributed across London, Poland, and Ukraine — acting as one team, not a satellite office. What sets us apart: * Led by an
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