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AI Training Roles We Staff
Data Annotators
Our annotators deliver consistent data labeling and annotation across text, image, audio, and video, document edge cases clearly, and follow layered QA so your training sets stay clean and rework stays low.
RLHF Raters and Preference Evaluators
These reviewers run pairwise and side-by-side ratings using calibrated rubrics, producing alignment data that reflects real customer tasks and improves model behavior.
Prompt Specialists and Prompt Engineers
Our prompt experts build and maintain prompt libraries, add practical guardrails and refusal handling, and run controlled A/B tests to raise task success and reduce deflections.
Model Evaluators
Hire model evaluators to design task-specific test sets, create dashboards, and maintain error taxonomies and release notes so product and research teams can ship with clear evidence.
Safety Reviewers and Red Team
This group probes models with adversarial prompts, checks policy conformance, and logs reproducible issues with mitigation steps so risks are surfaced before launch.
AI Research Assistants
Research assistants handle literature reviews, dataset operations, and experiment tracking, keeping documentation tidy and helping teams move faster with durable artifacts.
Human-in-the-Loop Project Leads
HITL leads plan the work, coach reviewers, set and monitor IAA targets, and manage escalations so throughput scales while quality stays steady.
Localization and Multilingual Reviewers
These reviewers validate outputs across target languages and locales—checking translation quality, cultural context, and policy nuances—so your model behaves correctly in every market you serve.
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