Applied ML Engineer Engineering London

You will own models that sit at the centre of a carrier's commercial workflow — recommending prices, quantifying confidence and learning from every accept-or-override. This is applied work: the measure of success is revenue moved and recommendations accepted, not papers published.You'll work end-to-end, from joining rate, capacity, booking and contract data into a single weighted view, through to the calibration and guardrails that make a recommendation defensible enough to send to a customer.What you'll doDesign, train and ship forecasting and recommendation models against real carrier rate, capacity and booking data.Build the confidence and explainability layer so every recommendation carries its rationale and a confidence band.Turn the override loop into training signal — every accept, adjust or reject makes the system sharper.Partner with deployment engineers to calibrate models against the rules trade managers actually use.Own model quality in production: monitoring, drift detection, retraining and the guardrails that keep outputs safe.What we're looking for4+ years building and shipping ML systems that ran in production, not just notebooks.Strong Python and the modern ML stack; comfortable owning a model from data to deployment.A bias for measurable business impact over model elegance.Clear written and verbal communication — you can explain a recommendation to a commercial team.Nice to haveExperience with time-series forecasting, pricing or demand models.Exposure to logistics, shipping, travel or other yield-managed industries.Comfort working directly with customers during a deployment.About SolvoSolvo.ai builds the decision layer for revenue management in container logistics. Container shipping moves $14 trillion of goods a year, yet the pricing decisions that move it still run on spreadsheets, gut feel and lag. We sell repeatable commercial outcomes — measured in revenue per TEU, not dashboards opened.We're a global, technical team spread across Cambridge, London and Singapore, backed by Sequoia, Speedinvest and Frontline, and already live with top-tier carriers. You'll work directly with the people who've sat in the trade room and the engineers building the system that learns from them. #J-18808-Ljbffr