Ocean Infinity
AI Engineer

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At Ocean Infinity
We're on a bold mission to revolutionize subsea data using innovative technology.
Using cutting-edge robotics, autonomous technology, and world-class software, we're transforming how complex operations are carried out at sea. Our uncrewed systems are making ocean exploration and operations safer, smarter, and more sustainable, helping unlock the vast potential of our oceans while reducing environmental impact. 🌍
This isn't a vision for the future. It's happening right now.
As we continue to push the boundaries of innovation and redefine what's possible in the maritime industry, we're looking for exceptional talent to join our fast-growing team.
Ocean Infinity is looking for 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 largely untapped field.
What you will do! 🤖
- 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What we look for!🔍
- 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.


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Nice to have! ✨
- Experience with self-supervised learning approaches such as DINO-style training, or joint embedding predictive architectures (JEPA).
- Familiarity with foundation models and their adaptation for domain-specific tasks via fine-tuning or few-shot methods.
- Experience working with sonar, magnetometer, acoustic, or other remote-sensing data types.
- Knowledge of MLOps practices including experiment tracking, model versioning, containerisation, and CI/CD pipelines.
- Publications or contributions to the research community through journals, conferences, Kaggle competitions, or open-source projects.
Salary £85,000 - £90,000 Per Annum
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