AI engineer in maritime in London

AI engineer in maritime in London

London Full-Time 72000 - 88000 £ / year (est.) Hybrid
RightShip

At a Glance

  • Tasks: Join our Product team to develop innovative AI solutions for maritime challenges.
  • Company: Dynamic maritime tech company focused on safety and sustainability.
  • Benefits: Competitive salary, Healthy Living Allowance, and strong professional development support.
  • Other info: Collaborative environment with opportunities for growth and mentorship from experienced professionals.
  • Why this job: Make a real impact in maritime safety while working with cutting-edge AI technologies.
  • Qualifications: 3+ years in AI/ML or software engineering, strong Python skills, and experience with LLM applications.

The predicted salary is between 72000 - 88000 £ per year.

We are growing the AI capability within our Product team and are looking for an AI Engineer to join us in London. This is an applied, experimental role that sits inside the Product team rather than a central engineering function. You will work directly with Product Managers to understand the problems our customers face, shape those problems into candidate AI solutions, and prove or disprove them quickly through prototypes, experiments and rigorous evaluation.

Responsibilities:

  • Work directly with Product Managers to gather and refine requirements, and translate them into candidate AI solutions with clear success criteria and evaluation plans.
  • Rapidly prototype and experiment with LLM-based applications, agents and retrieval pipelines to establish whether an idea works before it is committed to the roadmap.
  • Propose and document solution architectures, covering model choice, orchestration, data access, guardrails, and cost and latency trade-offs.
  • Design and build AI evaluation suites, offline and online, that define what good looks like for each feature and can be run in production to monitor quality over time.
  • Produce production-ready code with tests, evals, documentation and observability, hand it over to the engineering teams for productionisation, and support them through that transition.
  • Build and maintain retrieval and embedding pipelines over maritime data such as inspection reports, vessel records, documents and the RightShip knowledge graph.
  • Apply Responsible AI practice: traceability, guardrails, assessment of failure modes and bias, and alignment with RightShip's AI risk management framework.
  • Present experimental results and recommendations clearly to product, engineering and senior stakeholders.
  • Contribute to the AI team's shared tooling, patterns and standards; review code and share knowledge with colleagues.
  • Keep abreast of developments in models, agent frameworks and evaluation methods, and assess which are worth adopting.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics or a related field, or equivalent practical experience.
  • 3+ years of hands‑on AI/ML or software engineering experience, including LLM-based applications that have reached production.
  • Strong Python and software engineering fundamentals: testing, packaging, version control, code review and CI.
  • Demonstrated experience building agentic systems and RAG pipelines with LangGraph (and LangChain or similar), including tool use, state management and structured outputs.
  • Comfortable working in an experimental setting where requirements are loosely defined and part of the job is working out what to build.
  • Excellent communication skills, including explaining technical trade-offs to non-technical colleagues.

Desirable:

  • Experience designing and running LLM evaluations: building evaluation datasets, choosing metrics, LLM-as-judge, regression testing and monitoring quality in production.
  • Practical knowledge of embeddings, vector search and hybrid retrieval.
  • Experience deploying AI workloads on Azure, for example Azure OpenAI / AI Foundry, Azure AI Search and Functions or Container Apps.
  • Experience with Databricks (MLflow, Delta Lake, model serving).
  • Solid ML fundamentals; exposure to PyTorch or classical ML is useful but not central to this role.
  • Experience with multi-modal models, particularly document and image understanding.
  • Familiarity with graph databases (Neo4j, Cypher) or knowledge graphs.
  • Experience in maritime, shipping, logistics or another safety- or compliance-driven domain.
  • Open-source contributions or a public portfolio of work.

Conditions:

We offer a place where you know you are contributing to an organization who are constantly working to ensure ships are safe as possible so that crew and cargo are protected. We are passionate about maritime efficiency, safety and sustainability practices. Our base salary is competitive, we support employee wellbeing and provide our employees with a Healthy Living Allowance and our annual incentive scheme is awesome. We have some great talent who are happy to share their experience and skills to help you on your way and we are committed to professional development to make sure your career keeps growing while you’re working with us.

AI engineer in maritime in London employer: RightShip

RightShip is an exceptional employer that prioritises employee wellbeing and professional development, making it an ideal workplace for those passionate about the maritime industry. With a strong focus on fostering strategic relationships and driving growth, employees are encouraged to thrive in a collaborative environment that values innovation and personal growth. Located in a vibrant sector, RightShip offers unique opportunities to make a meaningful impact while enjoying a competitive salary and a supportive work culture.

RightShip

Contact Details:

RightShip Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI engineer in maritime in London

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at RightShip or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to RightShip.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like RightShip.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like RightShip that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace AI engineer in maritime in London

AI/ML Experience
Python Programming
Software Engineering Fundamentals
LLM-based Applications
Agentic Systems Development
RAG Pipelines with LangGraph
Experimental Prototyping

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at RightShip.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at RightShip and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at RightShip

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If RightShip uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.