At a Glance
- Tasks: Lead AI initiatives, develop cutting-edge computer vision models, and mentor a dynamic data science team.
- Company: Join a pioneering tech firm revolutionising AI with a collaborative and innovative culture.
- Benefits: Remote work, competitive salary, and opportunities for professional growth in a fast-paced environment.
- Other info: Be part of a global scaling journey with excellent career advancement opportunities.
- Why this job: Make a real impact in AI while working on groundbreaking projects that shape the future.
- Qualifications: Strong Python skills, machine learning experience, and a passion for computer vision.
The predicted salary is between 70000 - 90000 £ per year.
Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy. They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert tagged images. Now, they’re scaling globally — and need a world-class Lead AI Engineer to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges.
Role Overview
They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions.
Key Responsibilities
- Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning)
- Fine-tune, evaluate, and productionise multi-modal LLMs for business applications.
- Drive experimentation and prototyping of advanced ML/AI techniques
- Provide technical direction, mentoring, and hands-on guidance to the data science team.
- Work with engineering, product, and business stakeholders to align ML strategy with business goals.
- Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability, reproducibility, and monitoring of deployed models.
Requirements
- Strong, current Python, including building and maintaining production services with FastAPI or similar.
- Solid machine learning and computer vision background, with real models shipped to production rather than only notebooks and prototypes.
- Hands-on experience with a computer vision training and labelling toolchain such as Roboflow, including dataset management and model evaluation.
- Experience with Azure AI services such as Azure AI Foundry and Azure OpenAI, or a clear track record on an equivalent cloud AI stack and the ability to pick ours up quickly.
- Practical understanding of working in a regulated or compliance-sensitive environment: data residency, de-identification, model governance, auditability, and why explainability matters.
- The judgment to scope and lock a problem before building it, and to know when a model is good enough to ship.
- OpenCV and classical computer vision alongside deep learning.
ALL APPLICANTS MUST BE FREE TO WORK IN THE UK
Lead AI Engineer - Remote in London employer: Exposed Solutions
As a leading innovator in the AI sector, our client offers a dynamic and inclusive work environment that fosters creativity and collaboration. With a strong commitment to employee development, they provide ample opportunities for growth through mentorship and cutting-edge projects, all while working remotely from anywhere in the UK. Join a team that is not only pushing the boundaries of technology but also prioritising a culture of support and excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer - Remote in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Exposed Solutions!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Exposed Solutions.
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We think you need these skills to ace Lead AI Engineer - Remote in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Exposed Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Exposed Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Exposed Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Exposed Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
