GenAI & AI Systems Engineer — Production ML in Edinburgh

GenAI & AI Systems Engineer — Production ML in Edinburgh

Edinburgh Full-Time 80000 - 100000 £ / year (est.) No working from home possible
Gazelle Global

At a Glance

  • Tasks: Build intelligent AI solutions and enhance real-time decision making.
  • Company: Gazelle Global, a leader in AI-powered capabilities across industries.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic work environment with a focus on innovation and career advancement.
  • Why this job: Join a cutting-edge team and make a significant impact in AI technology.
  • Qualifications: Experience in AI systems, MLOps, and collaboration with data scientists.

The predicted salary is between 80000 - 100000 £ per year.

Gazelle Global is seeking an AI Engineer to build intelligent AI-powered capabilities across data‑rich industries.

You will deliver production‑ready AI solutions, leveraging Gen AI, LLMs, and RAG pipelines to enable real‑time decision making and scalable enterprise workflows.

You will partner with data scientists to productionize models, implement robust MLOps, and ensure secure, compliant AI systems while advancing observability and performance across cloud platforms.

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GenAI & AI Systems Engineer — Production ML in Edinburgh employer: Gazelle Global

Join a leading organisation at the forefront of cyber security transformation in London, where you will play a pivotal role in delivering critical initiatives. Our collaborative work culture fosters innovation and growth, offering ample opportunities for professional development and advancement within a dynamic environment. With competitive rates and a commitment to employee well-being, we ensure that our team members thrive both personally and professionally.

Gazelle Global

Contact Details:

Gazelle Global Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land GenAI & AI Systems Engineer — Production ML in Edinburgh

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 Gazelle Global!

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 GenAI & AI Systems Engineer — Production ML at Gazelle Global.

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 Gazelle Global.

Apply Directly through Our Website

When you find a suitable opening like GenAI & AI Systems Engineer — Production ML at Gazelle Global, 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 GenAI & AI Systems Engineer — Production ML in Edinburgh

GenAI
LLMs
RAG pipelines
MLOps
AI Systems Engineering
Real-time Decision Making
Cloud Platforms

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 Gazelle Global, 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 Gazelle Global. 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 Gazelle Global

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 Gazelle Global!

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.