At a Glance
- Tasks: Build and deploy cutting-edge AI applications that transform the way people work.
- Company: Join a forward-thinking organisation investing heavily in AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Make a real-world impact while working with the latest advancements in Generative AI.
- Qualifications: Experience in AI applications, strong Python skills, and a passion for machine learning.
The predicted salary is between 63000 - 77000 £ per year.
We're working with an organisation that’s making a significant investment in AI, building intelligent products that are transforming the way people work.
As part of a growing engineering team, you’ll play a key role in designing and delivering production AI applications with real-world impact.
This is a hands‑on opportunity for someone who enjoys taking ideas from concept through to deployment while working with the latest advancements in Generative AI.
The Role
- Build and deploy production‑grade AI applications using modern LLMs.
- Design scalable AI solutions that solve complex business challenges.
- Evaluate and improve model performance through experimentation and testing.
- Work closely with users to iterate quickly and deliver high‑quality products.
- Keep up to date with the latest developments across the AI ecosystem.
What We're Looking For
- Commercial experience building AI applications with LLMs.
- Strong Python engineering skills and experience shipping production code.
- Experience with RAG, prompt engineering, model evaluation or fine‑tuning.
- Knowledge of modern front‑end technologies is beneficial.
- Strong understanding of machine learning fundamentals.
- Degree in Computer Science, Mathematics or another quantitative discipline (or equivalent industry experience).
- Experience with cloud platforms and modern engineering practices is a plus.
- #J-18808-Ljbffr
AI Engineer employer: Harrington Starr
Join a leading high-volume futures trading organisation in London, where you will play a pivotal role in ensuring the stability of critical trading and clearing platforms. With a strong focus on employee growth and a collaborative work culture, this company offers competitive daily rates and long-term contract opportunities, making it an excellent employer for those seeking meaningful and rewarding careers in the capital markets sector.
StudySmarter Expert Advice🤫
We think this is how you could land AI 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 Harrington Starr!
✨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 Engineer at Harrington Starr.
✨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 Harrington Starr.
✨Apply Directly through Our Website
When you find a suitable opening like AI Engineer at Harrington Starr, 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 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 Harrington Starr, 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 Harrington Starr. 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 Harrington Starr
✨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 Harrington Starr!
✨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.
