Code Data Annotation Quality Specialist
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Key details
What makes this role novel
Data annotation quality roles focused on LLM training have emerged as a distinct specialization in the last 3 years, driven by the rapid scaling of large language models and the critical need for high-quality training data.
Job Description
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.
We are creative, low-ego and team-spirited.At Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit.
Mistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI.
Role SummaryWe’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.
Audit details(provenance, verification trail, raw fields)
Core fields
mistral:bd88179e-de69-4675-8a6c-74e2547a85acProvenance
mistralVerification trail
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