Autonomous Ocean AI Engineer

Ocean Infinity

Greater London

On-site

GBP 85,000 - 90,000

Full time

8 days ago

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Job summary

Ocean Infinity in Greater London is seeking an AI Engineer to join our growing AI team, applying cutting-edge AI to underwater sensor data including sonar, magnetometer and acoustic systems. You'll tackle high-impact challenges across ocean survey, maritime operations, asset monitoring and autonomous vessels, building production-ready AI solutions that deliver real-world impact.

This is a hands-on, high-autonomy role offering the opportunity to shape the future of AI in a rapidly evolving and

Qualifications

You have a degree in Computer Science, Mathematics, or a related field. A PhD or research background in Machine Learning or underwater sensor processing algorithms is a strong plus.
You have evidence of hands-on experience in AI and Machine Learning.
You are a solid Python developer with strong experience in PyTorch, TensorFlow, or similar deep learning frameworks.
You have experience working with non-standard imagery data. Writing custom data loaders and curating custom datasets.
You write clean, maintainable code and hold software engineering quality to the same standard as model performance.
You are comfortable operating with high autonomy in ambiguous, evolving environments and can break large problems into deliverable increments.
You communicate effectively with both technical and non-technical stakeholders and can explain complex AI concepts clearly

Responsibilities

Contribute to the design and delivery of AI solutions, taking projects from exploratory research through to production-ready inference pipelines.
Define the technical approach for complex AI projects, making decisions on model architectures, data strategies, evaluation frameworks, and deployment paths.
Design and implement models for detection, classification, prediction, and feature extraction.
Work with large-scale, often unlabelled datasets and apply self-supervised and semi-supervised learning techniques to build robust models.
Adapt and fine-tune foundation models, with techniques such as active learning for domain specific challenges in maritime AI.
Review code, define best practices, and champion high engineering standards across the AI team.
Communicate technical progress, trade-offs, and results clearly to both technical and non technical stakeholders.