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- Tasks: Help improve AI systems by providing feedback and evaluating code quality.
- Company: Join a leading enterprise client focused on cutting-edge AI technology.
- Benefits: Fully remote work, flexible schedule, and project-based engagement.
- Other info: Work on exciting projects with varying workloads and no guaranteed hours.
- Why this job: Shape the future of AI by enhancing how it understands and optimises code.
- Qualifications: 2+ years in backend engineering or AI automation with strong analytical skills.
The predicted salary is between 50000 - 70000 £ per year.
An enterprise client is currently seeking experienced software engineers to contribute to improving advanced AI systems through human feedback. This work supports leading AI organizations in training large language models to better understand software development practices, debugging, and code quality. This is part of a cutting-edge initiative focused on enhancing how AI systems write, review, and optimize code in real-world scenarios. You’ll play a key role in shaping how AI models evaluate performance, detect issues, and generate reliable outputs. This opportunity is ideal for engineers who enjoy analyzing systems, improving code quality, and working on complex technical challenges. You will contribute to AI training projects by evaluating outputs, refining logic, and identifying potential vulnerabilities.
What You’ll Do:
- Develop objective, verifiable evaluation criteria (rubrics) for system performance
- Review system logs and execution paths to improve reliability and code quality
- Refactor code and optimize system behavior toward ideal outcomes
- Test systems for vulnerabilities, including data exposure and edge-case failures
- Provide detailed, high-quality feedback on system performance and outputs
Requirements:
- 2+ years of experience in backend engineering, AI automation, or systems integration
- Experience working with SQL databases
- Proven ability to build and maintain production-grade systems
- Experience working in live (non-mocked) environments with multi-step interactions
- Strong analytical skills and attention to detail
Nice to Haves:
- Experience with multi-stage system workflows and coordination tasks
- Familiarity with integrating tools such as APIs, databases, or external platforms
- Understanding of system vulnerabilities (e.g., privacy leaks, prompt injection, access escalation)
- Experience working with AI systems or agent-based workflows
- Comfort working with persistent state tracking or similar frameworks
Additional Information:
- Fully remote and flexible work schedule
- Project-based engagement with no guaranteed hours
- Work on tasks based on availability and project assignment
- Payment is based on completed tasks only
- Must accept project invitations before beginning work
- No guaranteed workload; volume may vary weekly
Copy of AI Code Reviewer & Systems Evaluation Engineer 1 employer: Lifted, an Upwork Company™
Contact Detail:
Lifted, an Upwork Company™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Copy of AI Code Reviewer & Systems Evaluation Engineer 1
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with AI or systems evaluation. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those related to backend engineering or AI systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with SQL databases and system vulnerabilities. We want to see how you think and solve problems, so practice explaining your thought process!
✨Tip Number 4
Don’t forget to 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 engage directly with us.
We think you need these skills to ace Copy of AI Code Reviewer & Systems Evaluation Engineer 1
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the role. Highlight your experience in backend engineering and any work you've done with AI systems. We want to see how your skills align with what we're looking for!
Show Off Your Analytical Skills: Since this role involves evaluating system performance, be sure to showcase your analytical skills in your application. Mention specific projects where you’ve improved code quality or identified vulnerabilities. We love seeing real examples!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for your achievements and make it easy for us to see your qualifications at a glance. We appreciate straightforward communication!
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. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Lifted, an Upwork Company™
✨Know Your Stuff
Make sure you brush up on your backend engineering skills, especially around SQL databases and AI automation. Be ready to discuss your past experiences in detail, particularly any projects where you improved code quality or optimised system behaviour.
✨Showcase Your Analytical Skills
Prepare to demonstrate your analytical thinking during the interview. Think of examples where you've evaluated system performance or identified vulnerabilities. Use specific metrics or outcomes to highlight your contributions.
✨Familiarise with AI Systems
Since this role involves working with advanced AI systems, it’s a good idea to familiarise yourself with how these systems operate. Brush up on concepts like multi-stage workflows and system vulnerabilities, as these will likely come up in conversation.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare some thoughtful questions about the company’s approach to AI training projects and how they evaluate system performance. This shows your genuine interest and helps you assess if the role is right for you.