At a Glance
- Tasks: Design and deploy cutting-edge AI solutions that drive real business value.
- Company: Join a global leader in AI technology with a collaborative culture.
- Benefits: Up to £82,000 salary, bonus, 28 days holiday, and private medical insurance.
- Other info: Dynamic role with excellent career growth and modern tech stack.
- Why this job: Make a genuine impact in the fast-paced world of AI and ML.
- Qualifications: Experience in deploying machine learning models and working with Azure technologies.
The predicted salary is between 80000 - 100000 £ per year.
If you're an AI Engineer who wants to build production AI solutions rather than endless proof of concepts, this is an opportunity to help shape how enterprise AI is adopted across a global organisation. You'll be responsible for designing, deploying and optimising machine learning models, LLM-powered applications and agentic AI workflows within Microsoft Azure.
Working alongside platform engineers, data scientists and data engineers, you'll help move AI from experimentation into secure, scalable products that deliver real business value. This is an engineering role with genuine ownership. You'll be involved throughout the AI lifecycle, from designing and deploying solutions through to monitoring, optimisation and governance. You'll also work with modern AI technologies and help influence how they're adopted across the wider business.
You'll be working with technologies including Azure Databricks, Azure Machine Learning, Azure AI Foundry, LangChain, LangGraph and Python, building enterprise AI applications using RAG, vector databases, prompt orchestration and tool-calling patterns.
You'll need experience with:
- Deploying LLMs and machine learning models into Azure enterprise environments.
- Azure Databricks, Azure Machine Learning and ideally Azure AI Foundry.
- Building production AI applications using LangChain, LangGraph and Python.
- MLOps / LLMOps including deployment, monitoring, governance and lifecycle management.
- RAG, vector databases, prompt engineering and tool-calling patterns.
- Building end-to-end AI/ML pipelines from data preparation through to production.
- Working with technical and business stakeholders to deliver AI solutions.
Desirable experience includes MLflow, MCP, Docker, Kubernetes, GitLab CI/CD and Azure Data Factory.
What's on offer:
- Up to £82,000 salary
- Annual performance bonus
- 28 days' holiday plus bank holidays, with the option to buy more
- Private medical insurance
- Excellent pension, life assurance and a flexible benefits package
If you're already working in AI and want to spend more time building modern, production-ready LLM and agentic AI solutions using one of the strongest Azure AI stacks available, this role offers the chance to make a genuine impact while continuing to develop with a fast-moving technology landscape.
AI/ML Engineer in London employer: Talent Locker
As an AI/ML Engineer at our London-based company, you'll be part of a dynamic team that values innovation and collaboration, offering you the chance to work on cutting-edge AI solutions that drive real business impact. With a competitive salary, generous benefits including private medical insurance and a flexible holiday policy, we prioritise employee well-being and professional growth in a supportive hybrid work environment. Join us to not only advance your career but also to contribute to shaping the future of enterprise AI within a global organisation.
StudySmarter Expert Advice🤫
We think this is how you could land AI/ML Engineer in London
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI/ML Engineer at Talent Locker.
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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 Talent Locker.
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We think you need these skills to ace AI/ML Engineer 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 Talent Locker, 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 Talent Locker. 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 Talent Locker
✨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 Talent Locker!
✨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.
