ML Engineer: AI-Driven Marine Vessel Optimisation

Economics Network; Southampton; Hybrid; GBP 55,000 - 75,000; Full time

Benefits offered by this job

Personal development budget £6,000

Job summary

Compute Maritime Ltd seeks a Machine Learning Engineer to embed physics-informed AI tools into NeuralShipper, a marine vessel design platform, as part of a KTP with the University of Southampton. You will translate research into viable software, validate CFD-based models, and develop optimisation workflows for vessel performance across concepts to operations.

The role requires strong Python and ML/DL experience, plus CFD tools like STAR-CCM+.

Qualifications

• MSc/MEng or PhD (desirable) in Machine Learning, AI, CFD, Hydrodynamics, Optimisation, or a related field.
• Experience applying ML and DL to engineering or physical systems.
• Strong programming in Python; C++/MATLAB desirable.
• Experience with DL frameworks (PyTorch, TensorFlow, or JAX).
• Experience with CFD tools such as STAR-CCM+.
• Understanding naval architecture, ship hydrodynamics, or design analysis.
• Experience in physics-informed ML, surrogate modelling, generative AI or design optimisation is desirable.
• Entrepreneurial mindset with ability to build commercial acumen alongside technical strength.

Responsibilities

• Translate and embed research into a commercially viable solution by managing work packages.
• Develop and validate fast, physics-informed models for ship resistance and propulsion using CFD and benchmark data.
• Design and implement multidisciplinary optimisation methods integrated into NeuralShipper as scalable software tools.
• Extend NeuralShipper to wind-assisted propulsion and rigid sail systems, validating with industry stakeholders.

Skills

Python

C++

MATLAB

PyTorch

TensorFlow

JAX

CFD

Hydrodynamics

Naval architecture

Generative AI

Design optimisation

Education

MSc/MEng

PhD

Tools

STAR-CCM+

Job description

Compute Maritime Ltd seeks a Machine Learning Engineer to embed physics-informed AI tools into NeuralShipper, a marine vessel design platform, as part of a KTP with the University of Southampton. You will translate research into viable software, validate CFD-based models, and develop optimisation workflows for vessel performance across concepts to operations.

The role requires strong Python and ML/DL experience, plus CFD tools like STAR-CCM+.