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- Tasks: Maximise automated content classification using advanced AI and LLMs to protect online users.
- Company: Join a leading tech firm dedicated to online safety and innovation.
- 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 creativity and continuous improvement.
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.
As a Risk Detection AI Engineer, you will utilise a deep understanding of the online risk landscape, as well as our risk detection capabilities, to assist in developing and optimising automated systems for identifying and classifying risks across various online platforms. Leveraging cutting‑edge techniques for LLM prompting, fine‑tuning for specific risk contexts, and combining AI outputs with other signals, you will work to enhance risk detection, discover new and creative applications of AI for classification, and support the design and continuous improvement of workflows and solutions to ensure efficient risk management and protection against many areas of online risk, prioritising innovative, automated AI deployment wherever possible.
AI Integration and Optimisation- Understands how risk discovery is done and data is collected
- Collaborates with senior team members to integrate existing or emerging AI technologies (LLMs, GenAI, behavioural signals) into Risk Detection workflows
- Designs and implements effective LLM Prompts and AI-based classification criteria for risk detection
- Conducts data quality checks and feature usage analysis to ensure AI models are receiving optimal input
- Provides input on the technical requirements and expected output of AI models to upstream Machine Learning and Data Science teams
- Documents AI/ML component behaviour and performance for internal stakeholders
- Supports 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
- 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 employer: Resolver
Contact Detail:
Resolver Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Risk Detection AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI and risk detection. This could be anything from GitHub repositories to case studies that highlight your problem-solving abilities and creativity in using LLMs.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding of the online risk landscape. Be ready to discuss how you would apply AI techniques in real-world scenarios, especially those relevant to the role of a Risk Detection AI Engineer.
✨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, it shows you’re genuinely interested in joining our mission to protect children and brands online.
We think you need these skills to ace Risk Detection AI Engineer
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 in real-world scenarios. Make it personal and relatable!
Tailor Your Experience: Make sure to highlight your relevant experience with Generative AI and scripting in Python. We love seeing how your background aligns with the role, so don’t be shy about showcasing your skills and projects that demonstrate your expertise.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Use bullet points if it helps convey your message better – we want to understand your qualifications quickly!
Apply Through Our Website: Don’t forget 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 our team at StudySmarter!
How to prepare for a job interview at Resolver
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Large Language Models and Generative AI. Be ready to discuss how you've used these technologies in past projects, especially in risk detection contexts. This will show that you understand the core of what the role is about.
✨Showcase Your Scripting Skills
Since scripting in Python is essential for this role, prepare to talk about your experience with it. Bring examples of scripts you've written for testing or analysis, and be ready to explain your thought process behind them. This will demonstrate your technical prowess.
✨Understand Risk Metrics
Familiarise yourself with key detection metrics like Precision, Recall, and F1-score. Be prepared to discuss how these metrics impact business decisions and how you've applied them in previous roles. This shows you can connect technical skills with real-world implications.
✨Stay Current with Tech Trends
The tech landscape is always changing, especially in AI. Make sure you’re up to date with the latest advancements and be ready to share your thoughts on emerging technologies. This will highlight your passion for the field and your commitment to continuous learning.
