Data Generalist

Rex.zone; Greater London; Hybrid; GBP 35,000 - 52,000; Full time

Benefits offered by this job

Remote work

Job summary

Rex.zone in the United Kingdom is seeking a mid-senior Data Generalist to support AI/ML training workflows remotely. You will perform strict data labeling, RLHF-related tasks, and LLM evaluation, ensuring high data quality across large datasets.

You will collaborate with globally distributed remote engineers, follow annotation guidelines, and contribute to QA processes to improve next-generation AI model performance.

Qualifications

• Proven success in data labeling and RLHF workflows.
• Experience evaluating large language models (LLMs).
• Strong analytical abilities with meticulous attention to detail.

Responsibilities

• Annotate data following strict guidelines for AI training.
• Perform high-fidelity named data labeling and QA checks.
• Collaborate with global remote engineering teams to maintain data quality.

Skills

Data labeling

RLHF workflows

LLM evaluation

Analytical skills

Attention to detail

Remote work

Job description

Explore full-time remote Data Generalist jobs in London for 2026 at Rex.zone. Power AI training pipelines through expert data labeling, RLHF evaluation, and quality assurance for large language models.

Core Responsibilities in AI/ML Training Workflows

Your day-to-day operations will revolve around strict annotation guidelines compliance and complex content safety labeling. You will execute high-fidelity named entity recognition tasks and manage diverse datasets to refine LLM training pipelines. By conducting continuous QA evaluation and collaborating with our global remote engineering teams, you will ensure that all data inputs meet the rigorous standards required for next-generation AI model performance improvement.

Required Skills And Qualifications

Ideal candidates for these mid-senior Data Generalist roles possess a deep, practical understanding of AI data operations. You must demonstrate proven success in data labeling, RLHF workflows, and large language model evaluation. Exceptional analytical skills, meticulous attention to detail, and the ability to thrive in a fully remote, full-time environment are critical. Previous experience working with specialized annotation vendors, BPOs, or leading AI tech startups is highly advantageous.