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- Tasks: Ensure top-notch data quality for AI models and design automated QA methods.
- Company: Leading AI company at the forefront of technology.
- Benefits: Top-tier salary, comprehensive health benefits, and supportive family leave.
- Why this job: Join a dynamic team and make a real impact in AI development.
- Qualifications: Strong Python skills and experience with large datasets required.
- Other info: Exciting opportunities for growth in a cutting-edge field.
The predicted salary is between 36000 - 60000 £ per year.
A leading AI company is seeking an engineer to oversee data quality for LLM post-training. The role includes designing automated QA methods, collaborating with researchers, and ensuring high standards for training data.
The ideal candidate will have strong Python skills, experience with large datasets, and a solid understanding of data quality impacts.
This position offers top-tier compensation, comprehensive health benefits, and supportive family leave policies.
Data Quality Engineer — LLM Post-Training & Evaluation employer: Reflection AI
Contact Detail:
Reflection AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Quality Engineer — LLM Post-Training & Evaluation
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data quality space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those involving large datasets. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for interviews by brushing up on automated QA methods. Be ready to discuss how you would ensure high standards for training data in real-world scenarios.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to get noticed and shows you're serious about joining our team.
We think you need these skills to ace Data Quality Engineer — LLM Post-Training & Evaluation
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python skills and experience with large datasets. We want to see how your background aligns with the role of a Data Quality Engineer, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data quality and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled data quality issues in the past. We’re looking for someone who can design automated QA methods, so any relevant experiences will definitely catch our eye!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Reflection AI
✨Know Your Data Inside Out
Make sure you understand the nuances of data quality, especially in relation to large language models. Brush up on your knowledge of automated QA methods and be ready to discuss how you've applied these in past projects.
✨Showcase Your Python Skills
Since strong Python skills are a must for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your approach to data manipulation, so practice coding challenges that focus on data quality.
✨Collaborate Like a Pro
This position involves working closely with researchers, so be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully worked with cross-functional teams to improve data quality or streamline processes.
✨Understand the Impact of Data Quality
Be ready to articulate why data quality matters, particularly in the context of LLMs. Think about specific instances where poor data quality affected outcomes and how you addressed those issues. This will show your depth of understanding and commitment to high standards.
