AI/ML Engineer: Predictive Safety & NLP for Maritime

MCD Systems Limited.; United Kingdom; Remote; GBP 90,000 - 130,000; Full time

Job summary

MCD Systems in Teesside, United Kingdom, is building a new predictive AI product from the ground up. You will own the AI/ML side, designing predictive models, NLP pipelines, and human-supervised competency scoring for an enterprise safety platform.

The initial project runs to March 2027 and aims to evolve into a SaaS solution for maritime operators and offshore energy, with an academic partner and external data collaborators.

Qualifications

• Hands-on experience deploying ML models in production.
• NLP experience with text classification or information extraction.
• Experience with predictive or risk modelling techniques.
• Ability to design data pipelines and ML infrastructure.
• Ability to work independently in a small team.

Responsibilities

• Design and build predictive risk models to flag at-risk workforce patterns ahead of incidents.
• Build NLP pipelines to extract structured intelligence from unstructured safety reports and near-miss data.
• Develop human-supervised competency assessment scoring, keeping a human in the loop rather than fully automating decisions.
• Define model accuracy, fairness and user-acceptance thresholds with the technical team and external pilot partners.
• Design the AI infrastructure: data ingestion pipelines, the model training environment and the model-integration API layer.
• Collaborate with an academic partner, a Teesside University Applied AI research group, on predictive model design.
• Work closely with external data partners to understand safety report formats and workforce data structures.

Skills

ML production

NLP

Predictive modelling

Data pipelines

APIs

Independent worker

Tools

Cloud platforms

Model deployment tooling

NLP tooling

Job description

MCD Systems in Teesside, United Kingdom, is building a new predictive AI product from the ground up. You will own the AI/ML side, designing predictive models, NLP pipelines, and human-supervised competency scoring for an enterprise safety platform.

The initial project runs to March 2027 and aims to evolve into a SaaS solution for maritime operators and offshore energy, with an academic partner and external data collaborators.