Vessel Performance Engineer (Data Quality)

About Us

DeepSea is a maritime technology leader, providing a unified optimisation platform that helps shipping companies cut fuel consumption, reduce emissions, and transform vessel performance across entire fleets.

Built on the most advanced maritime AI data pool in the world, DeepSea’s platform powers everything from vessel monitoring to advanced automation - helping clients achieve measurable results with clarity, speed and scale.

We are trusted by some of the world’s most forward-thinking ship owners and operators, and our team spans Greece, the UK, Armenia, Romania, Singapore and Japan. As the shipping industry undergoes enormous change, we are at the centre of that transition - helping our customers take control, reduce risk, and build competitive advantage.

Main Responsibilities

• Train machine learning models to predict and evaluate ship performance under varying weather and operational conditions.

• Validate ML model outputs using physics-based rules and marine engineering knowledge to ensure predictions are realistic and applicable to ship operations.

• Assess the quality, accuracy, and completeness of data collected from ship sensors, telegrams, AIS and other sources, identifying anomalies or inconsistencies that could impact ML model performance.

• Develop and maintain Python-based tools and frameworks to automate workflows, streamline processes, and enhance operational efficiency across the team.

• Work with data engineering teams to design and maintain robust data pipelines for processing real-time and historical ship data.

• Document data quality findings, model performance, and validation results, providing actionable insights to improve software and operational outcomes.

• Communicate and collaborate with internal stakeholders (product owners, AI engineers, customer success managers, MLOps engineers) to understand business needs and requirements and present complex concepts to non-technical audiences, including external stakeholders and customers..

• Investigate ML model outputs based on customer feedback, resolve customer queries or identify areas of improvement, and present results to internal and external stakeholders and customers.