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- Tasks: Help develop evaluation frameworks for cutting-edge generative AI models.
- Company: Join a forward-thinking tech company in London.
- Benefits: Competitive hourly rate and inclusive work environment.
- Why this job: Be part of an innovative team shaping the future of AI technology.
- Qualifications: Strong communication skills and basic knowledge of Python, Unix, and SQL.
- Other info: Great opportunity for career growth in a dynamic field.
The predicted salary is between 20 - 30 ÂŁ per hour.
Contract Duration: 23 March 2026 – 31 December 2026
Location: London, UK
Work Arrangement: On-site
Remuneration: ÂŁ25.00 Hourly Rate
Overview
Advancements in generative AI have progressed rapidly, but measuring the true quality of AI‑generated content remains a significant challenge. Small variations in model-generated images or videos can greatly affect user experience, highlighting the need for reliable, standardized evaluation methods. This role supports a team developing comprehensive evaluation frameworks—including manual human ratings, semi-automated assessments, and fully automated metrics—to measure the performance of advanced image and video generative models (e.g., text-to-image, image-to-video, text-to-video). The team is expanding and requires additional analysts to help prototype, refine, and scale these evaluation methodologies.
Key Responsibilities
- Collaborate with the core team to design and prototype human rating workflows and semi‑automatic evaluation protocols for generative AI models.
- Conduct small- to medium-scale in-house human rating sessions for complex or high‑impact evaluation scenarios.
- Partner with engineering teams to analyse evaluation outputs, identify model performance gaps, and summarise findings.
- Work with engineers to define required datasets, mine relevant data, and prepare high‑quality training sets for model iteration cycles.
- Support Program Delivery & Operations (PDO) teams in scaling validated evaluation protocols, including process coordination, auditing, and documentation.
Required Skills
- Strong verbal and written communication abilities.
- Excellent problem‑solving skills and interpersonal effectiveness.
- High attention to detail and an interest in experimental and investigative tasks.
- Ability to work independently and manage time effectively.
- Basic proficiency with Python, Unix, and SQL.
- Foundational understanding of computer vision and generative AI models.
Education & Preferred Experience
- Associate degree or equivalent training in Computer Science, Electronic Engineering, Physics, Bioinformatics, or another STEM field.
- Prior industry experience in software development or testing is advantageous.
- Research experience in areas such as human–computer interaction is a strong plus.
Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.
Infrastructure Engineer in London employer: Adecco
Contact Detail:
Adecco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Infrastructure Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions related to infrastructure engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable with your responses.
✨Tip Number 3
Showcase your skills! Create a portfolio or GitHub repository with projects that highlight your proficiency in Python, Unix, and SQL. This gives potential employers a tangible look at what you can do.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Infrastructure Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Infrastructure Engineer role. Highlight your relevant skills and experiences that align with the job description, especially your communication abilities and problem-solving skills.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python, Unix, and SQL. If you have any experience with computer vision or generative AI models, make it stand out! We want to see how you can contribute to our team.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless necessary. We appreciate a well-structured application that’s easy to read and gets straight to the point.
Apply Through Our Website: We encourage you 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’s super easy!
How to prepare for a job interview at Adecco
✨Know Your Tech
Brush up on your knowledge of Python, Unix, and SQL before the interview. Be ready to discuss how you've used these skills in past projects or roles, especially in relation to generative AI models.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities. Think of specific challenges you've faced in previous roles and how you tackled them, particularly in experimental or investigative tasks.
✨Communicate Clearly
Strong verbal and written communication is key for this role. Practice explaining complex concepts in simple terms, as you'll need to collaborate with both technical and non-technical team members.
✨Demonstrate Attention to Detail
Be prepared to discuss how you ensure accuracy in your work. Bring examples of how your attention to detail has positively impacted your projects, especially in data preparation or evaluation processes.
