Data Scientist / Machine Learning Engineer - AI at Massive Scale.

About LoopMe

LoopMe is an AI company solving one of advertising's hardest problems: making brand advertising actually measurable — and making it perform. Our platform runs patented machine learning models across billions of consumer signals in real time, optimising campaigns toward outcomes like purchase intent, brand lift, and foot traffic rather than proxy metrics like clicks. The result is 2–5x better performance than industry benchmarks, at scale.

We operate a high-load programmatic infrastructure — processing millions of ad requests per second with sub-200ms response times globally. This isn't a layer on top of someone else's stack; it's built from the ground up, in-house, by the team you'd be joining. Founded in 2012 and headquartered in London, we now have 400+ people across 19 cities and have sustained 40% revenue CAGR since 2018. The engineering problems here are real, the ownership is genuine, and the scale is significant.

Help us push AI further — and faster

LoopMe’s Data Science team 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, 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 experienced Chief Data Scientist who codes, leads, and listens
• Inclusive, supportive culture where ideas are heard and people stay
• Strong values: open communication, continual innovation, fair treatment, and high standards
• Track record of publishing award-winning research in automated bidding

Don’t just take our word for it — check our Glassdoor reviews (search “Data Scientist”) for a real view of the culture.

 What we offer:

• Flexible working schedule
• 1 month of work-from-anywhere
• Annual performance bonus
• English classes
• LoopMe Gives Back
• Learning & development support

 Hiring process:

1. Intro with Talent Partner
2. 30-min technical interview with Chief Data Scientist
3. Panel with 2 team members (technical, culture & collaboration)
4. Offer – usually within 48 hours of final round

 Are you ready to design and deploy AI systems that run at truly massive scale?