I'm Carlos Rivera, a bilingual (Spanish/English) human agent in the DMV — Washington DC, Maryland, and Virginia. AI companies hire me for what no model has: human judgment to decide which answer is the good one, cultural context in two languages to catch what sounds off, and real-world presence to verify what a screen can't check.
An AI generates a thousand responses per second. But generating isn't judging, translating isn't understanding and predicting isn't verifying. In that gap — exactly there — the human agent works.
Your model generates. I judge, correct, and label. Pick a task type and see what a "call" to the human agent looks like — the result comes back reviewed, consistent, and ready for training.
latency: same day, Eastern hours · throughput: 1 agent, or a full team via the network (see below)
Judgment, bilingual context, and real-world verification are hired like this: eight services, one standard — every delivery goes through human judgment and a second quality review before it comes back to your team.
Labeling and classification of text, audio, and images to train and fine-tune models, following your annotation guideline to the letter.
I compare your model's responses, rank them best to worst, and explain why — the human signal that turns a correct model into a useful one.
Real Spanish, not machine-translated: variants, idioms, and cultural context from the U.S. and Latin America that a model usually misses.
Audits of data and outputs from other annotators: sampling, cross-checking, and error reporting with patterns, not just isolated cases.
I go where AI can't: public places across DC, Maryland, Virginia, and New York, capturing the photos and 360° video your models and listings need — in person.
Tasting, listening, seeing, touching, smelling: I experience products the way only a human can, and describe them objectively — no sensor or model substitutes for that.
A professional designer's eye on your AI-generated visuals: images reviewed pixel by pixel, thumbnails that earn the click, and graphic design that actually holds up.
Human review of AI-generated marketing copy in Spanish and English, so it sounds natural — like a person wrote it, because a person checked it.
Submit your task — our AI dispatcher reviews it and assigns a human agent. Human client or AI agent, the intake is the same: describe what needs doing and the request enters the dispatch queue as JSON via POST /api/task-request. You get a confirmation, a human gets assigned, and the work comes back reviewed.
Northern Virginia is one of the largest technology and data-center corridors in the world, and Washington DC concentrates government, contractors, and AI companies. Having the human agent in the area means the same time zone, the same context — and in-person presence when the task demands it.
The federal capital and home to agencies, contractors, and AI teams working with the public sector. In-person availability for projects that require it.
The I-270 tech corridor and one of the largest Spanish-speaking communities in the region: real bilingual talent, recruitable in person.
Northern Virginia: Ashburn's "Data Center Alley" and the tech ecosystem of Arlington and Tysons. AI's infrastructure lives here — and so does its human agent.
I'm not an anonymous platform. I'm a person, with a name, a track record, and a local reputation to protect.
Professionally bilingual: an accountant by training, with years of experience in quality control and compliance — I served as a Radiation Safety Officer (RSO) and assistant lab manager, jobs where a judgment error is not an option. That same obsession with detail is what I bring to every AI training task.
I also run a local events business in the DMV: I know how to work with clients, keep schedules and answer for the result. When a task outgrows one person, I activate my network of bilingual agents — recruited and supervised by me.
Hyper-sensitive human senses — I catch what others miss. A slightly off tone, a word that doesn't quite fit, a detail in an image or a sound that's a fraction out of place: I notice the subtle errors other evaluators scroll right past. That's the level of perception your model's quality bar actually needs.
This isn't just one agent: it's a growing network of bilingual human agents across the DMV. AI companies hire the project; the network executes it; and every agent gets paid for their work.
This is RLHF in miniature. A user asked a question and the model gave two answers. Your job as the human agent: pick the best one. That, thousands of times over, is what trains an AI.
If you speak Spanish and English and live in DC, Maryland, or Virginia, you can work as a human agent from home: AI companies pay for annotation, evaluation, and quality-control tasks, and the network assigns you the ones that fit you.
Straight answers, the way the agent works.
The companies behind the AIs do — constantly. Every large model is trained and corrected with human work: annotators, evaluators, and reviewers. This page puts a face, a name, and a location on that work in the DMV, instead of hiding it behind an anonymous platform.
Message me on WhatsApp or by email with the task type, the volume, and your annotation guideline or criteria. I reply the same day during Eastern hours, we agree on a small test sample, and if the quality convinces you, we scale — with me alone or with the full network.
The AI companies and platforms that hire each project. The network coordinates the work and quality control, and each agent gets paid for the tasks they complete, at the project's rate. No magic promises: real work, paid by real clients.
No. You need to be truly bilingual (read and write well in Spanish and English), have a computer and internet, and pass a short test of judgment and instruction-following. The rest is trained.
The vast majority is remote. The network's advantage is that we're all in the DMV: when a project needs something in person — a recording, a test, a session — we can be there.
Because U.S. Spanish and the DMV's cultural context don't outsource well at random. A local agent understands how people talk here, works in your time zone, and answers under his real name.
