AI/ML Engineer β€” GenAI & RAG Production Solutions

AI/ML Engineer β€” GenAI & RAG Production Solutions

Full-Time 70000 - 90000 Β£ / year (est.) No working from home possible
Version 1

At a Glance

  • Tasks: Develop and deploy cutting-edge AI/ML solutions for transformative technology.
  • Company: Join Version 1, a forward-thinking tech company in Newcastle upon Tyne.
  • Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Dynamic team environment with exciting projects and career advancement opportunities.
  • Why this job: Be at the forefront of innovation and make a real impact with AI technologies.
  • Qualifications: Strong Python skills and experience with machine learning frameworks required.

The predicted salary is between 70000 - 90000 Β£ per year.

Version 1 is looking for a skilled AI/ML Engineer to join their Newcastle upon Tyne team. The successful candidate will develop and deploy machine learning and Generative AI solutions, ensuring optimal performance and integration into business systems.

The role requires expertise in AI application development and a passion for innovative technologies. A strong background in Python and machine learning frameworks is essential.

Join Version 1 and contribute to transformative technology solutions!

AI/ML Engineer β€” GenAI & RAG Production Solutions employer: Version 1

Version 1 is an exceptional employer that fosters a culture of innovation and collaboration in the heart of Newcastle upon Tyne. With a strong commitment to employee growth, we offer extensive training opportunities and a supportive environment where your skills in AI and machine learning can flourish. Join us to be part of a forward-thinking team dedicated to developing transformative technology solutions that make a real impact.

Version 1

Contact Details:

Version 1 Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land AI/ML Engineer β€” GenAI & RAG Production Solutions

✨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 Version 1!

✨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/ML Engineer β€” GenAI & RAG Production Solutions at Version 1.

✨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 Version 1.

✨Apply Directly through Our Website

When you find a suitable opening like AI/ML Engineer β€” GenAI & RAG Production Solutions at Version 1, 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/ML Engineer β€” GenAI & RAG Production Solutions

Python
SQL
Problem-Solving Skills
Data Engineering
Data Pipeline Development
API Integration
Attention to Detail

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 Version 1, 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 Version 1. 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 Version 1

✨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 Version 1!

✨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.