Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Evaluate AI models and develop frameworks to enhance their features.
- Company: Dynamic AI research company in Greater London with a startup vibe.
- Benefits: Competitive salary, flexible hours, and opportunities for professional growth.
- Why this job: Join a fast-paced team and contribute to groundbreaking AI innovations.
- Qualifications: Strong statistical analysis skills and knowledge of LLM evaluation methods.
- Other info: Exciting environment with the chance to shape the future of AI.
The predicted salary is between 36000 - 60000 £ per year.
An AI research company in Greater London is seeking a candidate for a role focused on evaluating AI models. The position involves conducting comparative analysis, developing evaluation frameworks, and collaborating with various teams to improve model features.
Ideal candidates will have strong statistical analysis skills and familiarity with LLM evaluation methodologies. The role is designed for those excited to thrive in a fast-paced startup environment and contribute to groundbreaking AI developments.
Staff Evaluations Scientist for Open-Weight Models employer: Reflection AI
Contact Detail:
Reflection AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Evaluations Scientist for Open-Weight Models
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those working on model evaluations. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your statistical analysis projects and any relevant evaluation frameworks you've developed. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your LLM evaluation methodologies and be ready to discuss them in detail. We want to see your passion for AI and how you can contribute to our team.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Staff Evaluations Scientist for Open-Weight Models
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your statistical analysis skills and any experience you have with LLM evaluation methodologies. We want to see how your background aligns with the role, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. Mention how your previous experiences can contribute to evaluating AI models and improving model features. It shows us you’re genuinely interested!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. This helps us understand your qualifications quickly!
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 Reflection AI
✨Know Your Models
Make sure you brush up on the latest AI models and evaluation methodologies, especially those related to LLMs. Being able to discuss specific models and their strengths or weaknesses will show your expertise and enthusiasm for the role.
✨Statistical Savvy
Since strong statistical analysis skills are a must, prepare to discuss your experience with data analysis tools and techniques. Bring examples of how you've used statistics to evaluate model performance in past projects.
✨Collaborative Spirit
This role involves working with various teams, so be ready to share examples of successful collaborations. Highlight how you’ve worked cross-functionally in the past and how you can contribute to a team-oriented environment.
✨Fast-Paced Mindset
Demonstrate your ability to thrive in a startup environment by sharing experiences where you adapted quickly to changes or challenges. Show that you're not just excited about AI, but also about the dynamic nature of the industry.
