Staff Machine Learning Engineer (£220,000 | RecSys | Python)

Location: London, 4 days in office (Shoreditch)

Salary: Up to £220,000 + Bonus + Compelling Equity

This role is with one of Dex’s trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they’re looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

About the company

We’re working with a high-growth, profitable technology company building a new category in performance marketing. Their platform rewards a global user base of tens of millions for engaging with digital products, creating a powerful acquisition channel for some of the world’s largest brands. The business has achieved significant scale and revenue without external funding and continues to grow rapidly across international markets.

The opportunity

This is an early hire into a newly forming London engineering team. You’ll work on a core problem at the heart of the business: predicting user value in real time and optimising personalised reward systems at scale. The role is hands‑on, with ownership across the full lifecycle, from modelling to production deployment and iteration.

What you’ll do

• Design, build, and scale production‑grade ML systems
• Develop real‑time models to predict individual user value (pLTV)
• Optimise personalised reward systems based on behaviour and market dynamics
• Identify and diagnose underperforming campaigns using causal inference
• Own end‑to‑end delivery: modelling, deployment, monitoring, and optimisation
• Apply statistical methods (A/B testing, regression, probability) to ensure robustness
• Align ML solutions with business priorities and commercial impact
• Partner with product and engineering to translate problems into data‑driven systems
• Contribute to technical direction and raise engineering standards

Types of problems you’ll be solving

• Real‑time valuation of users across tens of millions of data points
• Designing adaptive reward systems under behavioural drift and market shifts
• Understanding not just what is happening in campaigns, but why
• Balancing model accuracy, latency, and commercial outcomes at scale

You should have

• Strong experience building and deploying ML systems in production
• Deep understanding of statistics (A/B testing, regression, probability)
• Strong programming skills in Python and SQL
• Experience working with cloud‑based infrastructure
• Ability to operate in high‑scale, data‑intensive environments
• A product‑oriented mindset with focus on impact
• Strong communication skills across technical and non‑technical stakeholders
• Experience in adtech, monetisation, or gaming
• Familiarity with metrics such as pLTV, retention, or ROAS
• Understanding of incentive systems or user behaviour modelling

Tech environment

• Production ML systems operating at large scale
• Real‑time data pipelines and decision systems
• Cloud‑native infrastructure
• Strong emphasis on statistical rigour and causal inference
• Tight feedback loops between models and real‑world outcomes

Why it’s compelling

• Work on a genuinely difficult ML problem with immediate feedback loops
• Direct impact on a product used by tens of millions of users
• Profitable, high‑growth business with strong fundamentals
• Early‑stage London team with influence over technical direction
• High ownership and exposure to core business systems
• Competitive compensation with performance upside

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