Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Review and audit code annotations to ensure high-quality data for AI models.
- Company: Join Mistral, a dynamic team on a mission to democratise AI.
- Benefits: Competitive salary, equity, health insurance, and gym contributions.
- Other info: Exciting opportunities for career growth in a collaborative environment.
- Why this job: Make a real impact in AI while collaborating with a global team.
- Qualifications: Degree in computer science or relevant experience in software engineering.
The predicted salary is between 30000 - 40000 £ per year.
About Mistral
At Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia.
Role Summary
We’re seeking highly motivated Data Quality Specialists with strong analytical skills and a keen eye for detail to join our Human Data Annotation team within the Science organisation. This is a hybrid quality reviewing and tooling role: you'll spend the majority of your time reviewing and auditing code annotations against rubrics to ensure data used for training and evaluating AI models meets a high bar, and the remainder building, maintaining, and troubleshooting the internal tooling that annotators rely on day-to-day. You’ll collaborate closely with the annotators, technical program manager, and engineer stakeholders, and contribute to refining the guidelines and processes that shape how our data is produced.
Key Responsibilities
- Generate and validate high-quality data annotations, based on guidelines and continuous feedback, for the development and evaluation of AI models.
- Surface systemic issues, edge cases, and gaps in guidelines back to annotation operations and technical stakeholders.
- Produce annotations yourself when needed, modeling the quality bar expected of the team.
- Build and maintain internal tools and automation that streamline annotator workflows such as visualization dashboards, batch configuration scripts, output management utilities, and similar.
- Troubleshoot environment, tooling, and CLI/git issues for annotators on their local machines, liaising with IT and engineering as needed.
About You
- A degree in computer science, engineering, or a related field. Alternatively, 2 to 5 years of professional experience in software engineering, technical support, or developing tools.
- Hands‑on experience using code agents (e.g. Mistral’s vibe) in your own development workflow, and genuine interest in how they're evolving.
- Proficient in at least one programming language (e.g. Python, JavaScript, or similar), with enough breadth to read and reason about code across a few core languages.
- Able to apply consistent judgment against a rubric and surface edge cases, ambiguities, or gaps in guidelines.
- Sustained focus and accuracy on detail‑oriented, high‑volume review work.
- Comfortable working in a Unix‑like terminal: shell basics, package managers, environment setup, and git workflows (branches, merges, resolving conflicts).
- Able to troubleshoot local development environment issues (dependencies, virtual environments, paths, permissions) across common operating systems.
- Professional proficiency in English, with strong writing and comprehension skills.
Nice to have
- Prior experience in data annotation for AI/ML, especially LLM training (SFT, RLHF, preference data), evals/benchmarks, or agentic data.
- Experience building an annotation team through interviews and training.
- Experience supporting technical users or troubleshooting developer environments (internal tools support, DevRel, teaching assistant for coding courses, etc.).
- Fluency across multiple programming languages, or domain depth in one of: frontend, backend, DevOps, MLOps, data engineering.
- Familiarity with rubric‑based evaluation concepts, inter‑annotator agreement, or quality measurement for human‑labeled data.
- Experience developing, deploying, and managing internal tooling or automation scripts.
Benefits
- Competitive cash salary and equity.
- Food: Daily lunch vouchers.
- Sport: Monthly contribution to a Gympass subscription.
- Transportation: Monthly contribution to a mobility pass.
- Health: Full health insurance for you and your family.
- Parental: Generous parental leave policy.
- Visa sponsorship.
By applying, you agree to our Applicant Privacy Policy.
Code Data Quality Specialist employer: Mistral AI
Contact Detail:
Mistral AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Code Data Quality Specialist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Mistral. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects that highlight your coding prowess, make sure to share them. It’s a great way to demonstrate your capabilities beyond just a CV.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your experience with programming languages and troubleshooting environments, as these are key for the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Code Data Quality Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Code Data Quality Specialist. Highlight your analytical skills, programming experience, and any relevant projects that showcase your attention to detail. We want to see how your background aligns with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your skills can contribute to our team. Be sure to mention any experience you have with data annotation or tooling, as this will resonate with us.
Showcase Your Technical Skills: Since this role involves coding and troubleshooting, don’t forget to mention your proficiency in programming languages like Python or JavaScript. If you've worked with tools or environments similar to what we use, let us know – we love seeing that hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, it helps us keep track of your application better!
How to prepare for a job interview at Mistral AI
✨Know Your Code
Make sure you brush up on your programming skills, especially in languages like Python or JavaScript. Be ready to discuss your experience with code agents and how you've used them in your workflow. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Understand the Role
Dive deep into the job description and understand the key responsibilities. Be prepared to talk about your experience with data annotation and how you’ve ensured quality in previous roles. Highlight any specific projects where you’ve had to troubleshoot or improve processes.
✨Show Your Analytical Skills
Since this role requires a keen eye for detail, be ready to demonstrate your analytical skills. You might be asked to evaluate sample annotations or identify edge cases. Practise articulating your thought process when reviewing data to showcase your judgement against rubrics.
✨Familiarise Yourself with Tools
Get comfortable with Unix-like terminals and common development tools. If you have experience troubleshooting local environments or using version control systems like Git, make sure to mention it. This will highlight your technical proficiency and readiness to support annotators effectively.