RLHF Preference Annotator (Onsite, Manila)
Corpshore AI's onsite RLHF Preference Annotator role in Manila, Philippines pays annotators to compare AI model outputs against a rubric and produce ranked preference data for LLM alignment, on an hourly contract with no AI background required.
Manila is one of Corpshore AI's core English-language delivery hubs. As an onsite RLHF Preference Annotator, you'll compare pairs (or sets) of AI model responses against a structured rubric and produce the ranked preference data that foundation-model teams use to align large language models — the same category of work behind Corpshore AI's 4.2M-preference-pair alignment programs.
Key responsibilities
- Compare model outputs against a written rubric and record structured preference judgments in Jwuma
- Write concise rationale notes justifying each ranking decision
- Identify unsafe, biased, or low-quality model outputs and flag them per project guidelines
- Maintain consistency with gold-standard calibration sets
- Meet daily/weekly batch targets without sacrificing judgment quality
What we look for
- Excellent English reading comprehension and written communication
- Strong, consistent judgment when comparing nuanced or subjective content
- Comfortable with sustained, screen-based cognitive work
- Available onsite at the Manila hub on a standard shift schedule
- No AI/ML background required — rubric and platform training provided
Nice to have
- Background in writing, editing, journalism, teaching, or research
- Prior BPO, QA, or content-review experience
- Exposure to chatbots or generative AI tools as a user
Compensation and benefits
- Hourly contract pay via Jwuma, weekly payout
- Paid rubric and platform onboarding
- Growth path to Senior RLHF Annotator or QA Lead
- Onsite facilities at the Manila delivery hub
Common questions
What is an RLHF preference annotator and what do they do?
They compare pairs of AI model outputs against a rubric and rank which response is better, producing the labeled preference data used to align large language models through reinforcement learning from human feedback.
Do I need a technical background to work in RLHF at Corpshore AI?
No. Strong reading comprehension, written English, and sound judgment matter most; the rubric and Jwuma platform are trained on the job.
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