Machine Learning Engineer (up to £230k)

Dex; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Dex in London is building a compact, high-impact data and ML team. You will own the full ML lifecycle—from data pipelines to live model serving—shaping rewards, personalization and measurement. The role emphasizes delivering value with speed and rigorous experimentation.

You’ll contribute to ML infrastructure and work across problems from engagement to revenue, with a hands-on, end-to-end responsibility culture.

Qualifications

• Hands-on in production ML: you ship, monitor, and iterate models end-to-end.
• End-to-end ownership of the problem: data, model, and live serving in one flow.
• Strong grounding in statistics, including A/B testing and regression.
• Familiar with causal inference or uplift methods to measure impact.

Responsibilities

• Design and ship production ML models that drive engagement and earnings.
• Translate complex business problems into concrete ML formulations.
• Build and optimize reward and payout structures balancing user motivation with cost.
• Diagnose underperforming campaigns and implement fixes.
• Contribute to core ML infrastructure from training pipelines to live serving.

Skills

Production ML

End-to-end ML

Data pipeline

Model serving

AB testing

Statistics

Causal inference

ML infrastructure

Business impact

Job description

This company runs a bootstrapped rewards platform with 80 million users, profitable since day one. The models you build here directly decide what users see and what the company earns, offering a rare, direct line from your work to significant business impact. They are one of Europe's fastest-growing companies, expanding their data and ML function in London.

You'll join a deliberately small data and ML team, owning the entire surface end-to-end. This isn't a role where you hand off models; you'll design, ship, and diagnose them, with a short feedback loop measured in weeks. You'll also help build the ML infrastructure, not just consume it, across a range of problems from reward ranking to personalization and measurement.

The work

• Design and ship production machine learning models that directly impact user engagement and company earnings.
• Translate complex mathematical business problems into concrete ML formulations.
• Build and optimize reward and payout structures, balancing user motivation with cost sustainability and advertiser value.
• Diagnose and troubleshoot underperforming reward campaigns, identifying root causes and implementing solutions.
• Contribute to the design and implementation of the core ML infrastructure, from training pipelines to live model serving.

What You Bring

• You are genuinely hands-on in production ML, having shipped models end-to-end rather than handing them off.
• You work across the full stack of a problem: data pipeline, model, and live serving.
• You have a strong grounding in statistics, including A/B testing, regression, and probability, ideally with causal inference or uplift methods.
• You are motivated as much by business impact as by technical elegance, prioritizing high-leverage solutions.
• You want to build ML infrastructure alongside your team, not just use existing systems.

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