Role overview

Kpler is a global intelligence platform founded in 2014 that transforms complex trade data into actionable insights for the commodities, energy, and maritime sectors. As a Machine Learning Engineering Manager in the Power division, you will lead an engineering team focused on developing and deploying production-grade machine learning models that drive the company’s core trade intelligence platform.

Key responsibilities

Lead and grow an engineering team dedicated to building machine learning solutions that support global trade intelligence.
Guide your team in scaling resilient MLOps pipelines that handle real-time data processing at scale.
Oversee the deployment and maintenance of machine learning models that process massive, real-time datasets.
Bridge people leadership, system architecture, and applied AI to ensure your team delivers high-impact solutions.
Translate complex market telemetry into actionable signals for clients in the commodity and maritime sectors.

Requirements

Demonstrated experience leading engineering teams focused on machine learning and MLOps.
Strong background in system architecture and deploying production machine learning models at scale.
Expertise in building and maintaining resilient pipelines that handle real-time data processing.
Proven ability to combine people leadership skills with technical depth in applied AI and machine learning.

What makes this role worth considering

You will join a diverse team of over 850 experts spanning 69 countries, working on systems that directly impact decision-making for major players in global commodities and maritime markets. This role offers the opportunity to lead technical innovation at the intersection of large-scale data engineering and machine learning, working on problems that materially influence how organisations navigate complex international trade.