Graduate AI Engineer: Build Real AI for Clients (Hybrid)

Graduate AI Engineer: Build Real AI for Clients (Hybrid)

Full-Time 65250 - 79750 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build real AI for clients and develop data pipelines using Python.
  • Company: Fifty One Degrees, a leading UK AI and data consultancy.
  • Benefits: Hybrid work model, mentorship from senior engineers, and hands-on experience.
  • Other info: Join a dynamic team and grow your skills in an innovative environment.
  • Why this job: Kickstart your career by working on live projects from day one.
  • Qualifications: Background in Computer Science or Maths, with a passion for learning.

The predicted salary is between 65250 - 79750 £ per year.

Fifty One Degrees, a UK AI and data consultancy, is seeking a graduate engineer to join our team in a Python-first role.

You’ll work on live client projects from week one, with mentorship from senior engineers, and help build AI agents and data pipelines while learning the full lifecycle by shipping.

The role is hybrid, with at least one or two days a month in our London coworking offices.

We’ll assess your CS/Maths background, curiosity and appetite to learn quickly, and your eagerness to

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Graduate AI Engineer: Build Real AI for Clients (Hybrid) employer: Fifty One Degrees

Fifty One Degrees is an exceptional employer that fosters a dynamic and collaborative work culture, where graduate engineers can thrive while working on impactful AI projects from day one. With a strong emphasis on mentorship and professional development, employees are encouraged to grow their skills in a supportive environment, all while enjoying the flexibility of a hybrid work model in the vibrant city of London.

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Contact Details:

Fifty One Degrees Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Graduate AI Engineer: Build Real AI for Clients (Hybrid)

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 Fifty One Degrees!

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 Graduate AI Engineer: Build Real AI for Clients (Hybrid) at Fifty One Degrees.

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 Fifty One Degrees.

Apply Directly through Our Website

When you find a suitable opening like Graduate AI Engineer: Build Real AI for Clients (Hybrid) at Fifty One Degrees, 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 Graduate AI Engineer: Build Real AI for Clients (Hybrid)

Python
AI Development
Data Pipeline Construction
Client Project Experience
Mentorship
Full Lifecycle Understanding
Curiosity

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 Fifty One Degrees, 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 Fifty One Degrees. 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 Fifty One Degrees

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 Fifty One Degrees!

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.