At a Glance
- Tasks: Build and deploy cutting-edge AI and ML solutions while collaborating with top tech professionals.
- Company: Join a forward-thinking tech company investing in AI and Machine Learning.
- Benefits: Earn up to £75,000 with hybrid work, training, and career progression opportunities.
- Other info: Dynamic environment with exposure to modern technologies and supportive culture.
- Why this job: Make a real impact on innovative AI projects across various industries.
- Qualifications: Strong Python and SQL skills, plus experience with AI frameworks like TensorFlow or PyTorch.
The predicted salary is between 60000 - 80000 £ per year.
- AI & Machine Learning Engineer - Multiple Levels Available
- London (Hybrid) - Python, SQL, Tensor Flow, Py Torch - Azure, AWS & GCP - Up to £75,000
Our client is investing heavily in Artificial Intelligence and Machine Learning capabilities and is seeking talented AI professionals to join a growing technology team in London.
This is an opportunity to work on cutting‑edge AI solutions, develop enterprise‑scale machine learning applications and collaborate with highly skilled technical professionals delivering innovative outcomes for a range of organisations.
Whether you're looking to deepen your technical expertise or take on greater ownership and leadership responsibilities, this role offers exceptional development opportunities and clear career progression.
- You Will Work With
- Building and deploying AI and Machine Learning solutions
- Designing and implementing end-to-end AI and ML pipelines, from data acquisition and feature engineering through to deployment and optimisation
- Developing scalable ML pipelines and engineering frameworks
- AI model training, evaluation, optimisation and deployment
- Cloud-native AI and data platforms across Azure, AWS and GCP
- MLOps tools and best practices for deployment, monitoring and governance
- Structured and unstructured datasets
- Generative AI and advanced analytics solutions
- Designing and maintaining scalable data pipelines, datasets and workflows
- Collaborating directly with client stakeholders to understand business challenges and translate requirements into AI solutions
- Working closely with technical and non-technical teams throughout programme delivery
- Cross-functional engineering, architecture and data teams
- Agile software development and delivery methodologies
- Exploring and adopting emerging AI technologies and approaches to drive innovation and business value
Benefits
- Salary up to £75,000
- Hybrid and flexible working arrangements
- Access to cutting‑edge AI projects
- Professional certifications and ongoing training
- Structured career progression opportunities
- Exposure to modern technologies and large-scale programmes
- Supportive and collaborative culture
- Opportunity to work across a variety of industries
- Competitive benefits package
- Key Experience
- Experience building and deploying AI or Machine Learning solutions in a commercial environment
- Strong Python and SQL skills
- Experience using Tensor Flow, Py Torch, Scikit-learn or similar frameworks
- Strong understanding of machine learning algorithms, deep learning architectures and model deployment practices
- Experience with Azure, AWS or GCP cloud environments
- Knowledge of data engineering principles including ETL processes, data pipelines and automated workflows
- Experience working with structured and unstructured data
- Understanding of MLOps tooling and best practices
- Knowledge of data governance, security and compliance principles within AI and data environments
- Strong analytical and problem‑solving ability Experience working within Agile delivery environments
- Ability to work closely with stakeholders and translate business requirements into effective AI solutions
Desirable
- Generative AI experience
- Large Language Models (LLMs)
- Lang Chain or similar frameworks
- Spark, Hadoop or other big data technologies
- Experience with distributed computing, streaming platforms or workflow orchestration tools
- Experience monitoring and optimising model performance in production environments
- #J-18808-Ljbffr
AI & Machine Learning Engineer employer: Cyber Security training courses
As an AI Engineer at our Central London office, you will be part of a dynamic team dedicated to pioneering cutting-edge AI solutions that drive business growth and enhance engineering capabilities. We pride ourselves on fostering a collaborative work culture that encourages innovation and professional development, offering competitive salaries, performance bonuses, and the flexibility of a hybrid working model to ensure a healthy work-life balance.
Contact Details:
Cyber Security training courses Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI & Machine Learning Engineer
✨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 Cyber Security training courses!
✨Show Off Your Projects
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 & Machine Learning Engineer at Cyber Security training courses.
✨Leverage Professional Networks
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 Cyber Security training courses.
✨Apply Directly through Our Website
When you find a suitable opening like AI & Machine Learning Engineer at Cyber Security training courses, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI & Machine Learning Engineer
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 Cyber Security training courses, 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 Cyber Security training courses. 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 Cyber Security training courses
✨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 Cyber Security training courses!
✨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.
