Applied ML Engineer

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.

• Design, 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.

• 4+ 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.

• Experience 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.

Solvo.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, Speed invest 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.