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- Tasks: Join our team to ensure top-notch quality in AI detection systems through research, data analysis, and automation.
- Company: Turnitin is a leading tech company focused on maintaining integrity in academic and professional work.
- Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology, collaborating with diverse teams and making a real impact.
- Qualifications: 3+ years in web testing, automation, and data analysis; strong Python or Java skills required.
- Other info: Ideal for those passionate about AI and eager to innovate in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
The department of Quality Engineering (under Technology) plays a crucial role in the software development process. This department is primarily responsible for ensuring that software products being developed within the Technology org at Turnitin meet or exceed predetermined quality standards.
Responsibilities:
- Research: Stay updated on trends and techniques related to bypassing AI detection systems; proactively share relevant findings with the team.
- Data Analysis: Aggregate, organise, and analyse data to uncover patterns, trends, and vulnerabilities in AI detection mechanisms.
- Automation & Solution Strategy: Identify high-ROI automation opportunities for testing AI detection systems. Develop, maintain, and improve automated test coverage and contribute to overall solution design.
- Team Collaboration: Act as a central communication point between technical and non-technical team members to ensure alignment and information flow.
- Documentation & Process Improvement: Create, maintain, and regularly update clear documentation and reports covering methods, tools, test strategies, vulnerabilities, and impact assessments; continuously improve related processes to meet evolving needs.
- Knowledge Sharing: Provide guidance and occasional training to team members on recognising and responding to new bypass techniques.
Qualifications Requirements:
- 3+ years of combined experience in web application testing, automation, and data analysis.
- Proven ability to develop and maintain automated tests (using Python or Java, Pytest, REST Assured, or similar), including integration with REST APIs.
- Experience with prompt engineering and LLM APIs.
- Understanding of the ML lifecycle (training, fine-tuning, eval), Generative AI, and related technologies.
- Capable of analysing complex datasets to identify patterns, trends, and anomalies related to AI detection bypass techniques.
- Experience with version control (Git) and CI/CD pipelines.
- Experience with API testing.
- Excellent written and verbal English for effective cross-team communication, including with non-technical stakeholders.
- Working knowledge of Excel or Google Sheets (including formulas).
- Experience leading or mentoring teams in test automation initiatives.
Nice to Have:
- Exposure to security testing or red-teaming, especially related to NLP or AI systems.
AI Quality Engineer (UK Remote) employer: Korn Ferry
Contact Detail:
Korn Ferry Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Quality Engineer (UK Remote)
✨Tip Number 1
Familiarise yourself with the latest trends in AI detection systems and bypass techniques. This knowledge will not only help you during interviews but also demonstrate your proactive approach to staying updated in a rapidly evolving field.
✨Tip Number 2
Engage with online communities or forums related to AI quality engineering. Networking with professionals in the field can provide insights into the role and may even lead to referrals, increasing your chances of landing the job.
✨Tip Number 3
Prepare to discuss specific examples of your experience with automation and data analysis. Being able to articulate how you've identified high-ROI opportunities in past roles will showcase your value to the team.
✨Tip Number 4
Brush up on your communication skills, especially when it comes to explaining technical concepts to non-technical stakeholders. This is crucial for the role, and demonstrating this ability can set you apart from other candidates.
We think you need these skills to ace AI Quality Engineer (UK Remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in web application testing, automation, and data analysis. Emphasise your skills in Python or Java, as well as any experience with REST APIs and CI/CD pipelines.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role of AI Quality Engineer. Discuss your understanding of the ML lifecycle and how your background aligns with the responsibilities outlined in the job description.
Showcase Relevant Projects: If you have worked on projects involving AI detection systems or automation, be sure to include these in your application. Highlight specific outcomes and your contributions to demonstrate your expertise.
Proofread Your Application: Before submitting, carefully proofread your application materials. Ensure there are no grammatical errors and that your writing is clear and concise, especially since excellent communication skills are essential for this role.
How to prepare for a job interview at Korn Ferry
✨Showcase Your Technical Skills
Be prepared to discuss your experience with automation tools and languages like Python or Java. Highlight specific projects where you've developed automated tests, especially those involving REST APIs, as this will demonstrate your technical proficiency.
✨Demonstrate Data Analysis Expertise
Since the role involves analysing complex datasets, come equipped with examples of how you've uncovered patterns or trends in data. Discuss any relevant tools or methodologies you've used, such as Excel or Google Sheets, to showcase your analytical skills.
✨Emphasise Team Collaboration
This position requires acting as a communication bridge between technical and non-technical teams. Prepare to share experiences where you've successfully facilitated collaboration, ensuring that all team members are aligned and informed.
✨Prepare for Knowledge Sharing Scenarios
Expect questions about how you would guide and train team members on new techniques. Think of examples where you've mentored others or shared knowledge effectively, as this will highlight your leadership capabilities in a technical environment.
