Machine Learning Engineer

Want to build ML where you can actually see whether your decisions worked?

You’ll build the models and optimisation systems deciding how millions of dollars of advertising spend gets allocated across Meta, Google and TikTok.

Think ML meets quantitative trading , applied to digital advertising.

Why it’s interesting

• Your models will make real financial decisions
• Build everything from LTV models to budget optimisation
• Own the journey from idea and backtest to live production
• Work on problems involving forecasting, optimisation and automated decision-making
• Join early with plenty of ownership and influence

What you’ll be doing

• Building models to predict customer value and ad performance
• Developing algorithms to decide where and when to allocate budget
• Building systems that automatically execute those decisions
• Backtesting strategies before putting real money behind them
• Deploying and monitoring models in production
• Improving performance as markets and customer behaviour change

What you’ll bring

• 4+ years of applied ML experience
• Strong knowledge of statistics and probability
• Experience taking models into production
• Solid software engineering skills
• An interest in optimisation and decision-making systems
• A practical approach — sometimes the simple model is the right model

Experience in quant trading, optimisation or adtech would be a bonus.

If you want to build ML where performance is measured in real dollars, not just model accuracy , get in touch.