At a Glance
- Tasks: Train AI models by evaluating chatbots and solving coding challenges.
- Company: Join a forward-thinking tech team focused on AI innovation.
- Benefits: Flexible remote work, competitive pay, and performance bonuses.
- Other info: Ideal for detail-oriented individuals seeking growth in AI technology.
- Why this job: Shape the future of AI while working on exciting projects.
- Qualifications: Fluency in English and proficiency in programming languages required.
The predicted salary is between 40000 - 60000 £ per year.
We are looking for a Full Stack Developer to join our team to train AI models. You will measure the progress of these AI chatbots, evaluate their logic, and solve problems to improve the quality of each model.
Benefits:
- Full‑time or part‑time remote position
- You can choose which projects to work on and set your own schedule
- Paid hourly at $50‑75+/hr with performance bonuses
- Payment made via PayPal (no upfront fees, currency conversion handled by PayPal)
Responsibilities:
- Give AI chatbots coding challenges and evaluate their outputs
- Assess AI‑model quality for correctness and performance
Qualifications:
- Fluency in English (native or bilingual)
- Detail‑oriented
- Experience with algorithms, data structures, and debugging workflows
- Proficiency in at least one programming language (JavaScript, Python, C#, C++, HTML, SQL, or Swift)
- Bachelor’s degree preferred but not required
- Only applicants located in the United Kingdom will be considered
Full Stack Developer - AI Trainer employer: DataAnnotation
Join our innovative team as a Full Stack Developer - AI Trainer, where you can enjoy the flexibility of remote work while contributing to cutting-edge AI projects. We offer competitive hourly rates, performance bonuses, and the freedom to choose your own projects and schedule, fostering a supportive work culture that prioritises employee growth and satisfaction. With a focus on collaboration and continuous improvement, this role provides a unique opportunity to make a meaningful impact in the rapidly evolving field of artificial intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Full Stack Developer - AI Trainer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at DataAnnotation or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to DataAnnotation.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like DataAnnotation.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like DataAnnotation that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Full Stack Developer - AI Trainer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at DataAnnotation.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at DataAnnotation and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at DataAnnotation
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If DataAnnotation uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
