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- Tasks: Maximise automated content classification using advanced AI and LLMs to protect online safety.
- Company: Join a leading tech firm dedicated to safeguarding children and brands online.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real difference in online safety while working with cutting-edge AI technologies.
- Qualifications: Bachelor’s degree or equivalent experience in AI, scripting skills, and data analysis.
- Other info: Dynamic team environment with a focus on innovation and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
The role of a Risk Detection AI Engineer is to maximise the automated classification of millions of pieces of content that come through our platform by creatively applying and integrating advanced Large Language Models (LLMs) and other Artificial Intelligence capabilities. This is a role central to everything that we do to protect children, brands, and platforms online.
Responsibilities
- Understand how risk discovery is done and data is collected.
- Collaborate with senior team members to integrate existing or emerging AI technologies (LLMs, GenAI, behavioural signals) into Risk Detection workflows.
- Design and implement effective LLM prompts and AI-based classification criteria for risk detection.
- Conduct data quality checks and feature usage analysis to ensure AI models are receiving optimal input.
- Provide input on the technical requirements and expected output of AI models to upstream Machine Learning and Data Science teams.
- Document AI/ML component behaviour and performance for internal stakeholders.
- Support RD Config Engineers in the optimisation of workflows that incorporate AI models.
- Ability to adapt, refine, and execute scripts (e.g., Python) for testing, analysis, and validation of AI component integration.
Qualifications & Experience
- Bachelor’s degree or equivalent experience.
- Ability to input on the design and optimisation of solutions using advanced techniques like proprietary NLP, LLMs, GenAI, and behavioural signals.
- Experience with the use and implementation of Generative AI solutions.
- Ability to write effective LLM prompts for Risk Classification.
- Scripting experience (e.g., Python) is essential.
- Query language (SQL) desirable.
- Ability to work with high volumes of data.
- Good understanding of core detection metrics (e.g., Precision, Recall, F1-score) and their business implications.
- Proficient in compiling and interpreting confusion metrics.
- Knowledge of Resolver’s risk taxonomy.
- Knowledge of how data is collected for each product and overall data flow.
- Able to read and write JSON.
- Keeping up to date with emerging tech.
Risk Detection AI Engineer in Leeds employer: Resolver, a Kroll Business
Contact Detail:
Resolver, a Kroll Business Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Risk Detection AI Engineer in Leeds
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those involving AI and LLMs. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of risk detection metrics and AI integration. Be ready to discuss how you've used Python or SQL in past projects.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Risk Detection AI Engineer in Leeds
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and risk detection shine through. We want to see how you creatively apply your knowledge of LLMs and other AI technologies. Make it clear why this role excites you!
Tailor Your Experience: Don’t just list your qualifications; connect them to the job description. Highlight your experience with Generative AI, scripting in Python, and any relevant projects. We love seeing how your background aligns with what we do at StudySmarter.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your skills and experiences. We appreciate a well-structured application that makes it easy for us to see your potential fit for the team.
Apply Through Our Website: Make sure to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining the StudySmarter family!
How to prepare for a job interview at Resolver, a Kroll Business
✨Know Your AI Inside Out
Make sure you brush up on your knowledge of Large Language Models and Generative AI. Be ready to discuss how these technologies can be applied in risk detection. Think about specific examples where you've used or integrated these technologies in the past.
✨Showcase Your Scripting Skills
Since scripting in Python is essential for this role, prepare to demonstrate your coding skills. Bring along examples of scripts you've written, especially those related to data analysis or AI integration. Practise explaining your thought process behind the code.
✨Understand the Metrics
Familiarise yourself with core detection metrics like Precision, Recall, and F1-score. Be prepared to discuss how these metrics impact business decisions and how you’ve used them in previous projects. This shows you understand the bigger picture.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's approach to risk detection and how they integrate AI. This not only shows your interest but also helps you gauge if the company aligns with your values and career goals.
