capture program / 03 · kitchens and food service

AI training jobs for cooks and other restaurant workers. Your shift is the lesson. $12 per accepted hour.

Line cooks, prep cooks, pastry bakers, baristas, bartenders, and dish crews clip a small camera to their chest, work the shift they were already scheduled for, and upload the footage. eeko pays $12 for every hour a reviewer accepts, separately from your wages and tips, and kitchen robots learn from watching someone who can actually cook.

$12 per accepted hour Recipes off limits Restaurant signs once Free to join
Hero image · 840 × 1050
per accepted hour
$12/hr
separate from wages and tips
kitchen roles open
9+
prep to pastry to dish pit
review turnaround
days
a few, with a note on every upload
first upload
paid
one hour, pass or fail

What is an AI training job for restaurant workers?

An AI training job for cooks and restaurant workers pays kitchen staff to record their ordinary shift from a first-person camera so that robots and AI models can learn from it. A kitchen is the hardest room in a building to automate: it is hot, wet, loud, and full of soft, slippery, irregular things that change shape as you cook them. A robot that has only seen tidy lab demonstrations has no idea how a cook portions a protein, reads a sauté pan, or keeps six tickets straight at 7:40 on a Friday.

eeko builds production AI for regulated enterprises, and the robotics and food-service models our clients are developing need training data nobody has published: consented, recorded by skilled people, and verifiable item by item. Our data capture practice exists to gather it, and this program sits alongside the others on our get paid to train AI hub. The kitchen program is the one for anyone whose shift happens behind a pass, a bar, a counter, or a dish machine.

You cook exactly as you cook now. The camera rides along, the restaurant signs one agreement, and the recipes stay in the binder.

One dinner service, from clock-in to breakdown.

An illustrative log for a line cook on the program. The review notes are the kind every upload gets back.

// friday-pm.log consent.log payout.log
tail -f
14:00 CLOCK IN Camera clipped at chest height, pointed at the board. Restaurant agreement on file; sauce station excluded by the owner.Consent: restaurant group agreement · exclusion zone: sauce station RECORDING
14:05 PREP Two hours of mise en place: breaking down cases of produce, dicing, portioning proteins, labeling and dating sixth pans.Review note: excellent, knife work fully visible 2h 00m ACCEPTED
16:10 PAUSE Family meal and a smoke break. Camera paused with the gesture from onboarding. Nothing recorded, nothing counted.Unrecorded time is not uploaded PAUSED
16:40 SERVICE Three hours on grill and sauté: firing tickets, timing proteins, plating to the pass, wiping rims. Twelve minutes trimmed when a printed prep sheet filled the frame.Blur applied · 12 minutes not counted 2h 48m ACCEPTED
21:50 BREAKDOWN Station breakdown, wrapping and labeling, scrubbing flat-top, running the last pans through the dish machine with the dishwasher.Review note: coworker's face blurred in two passes 1h 05m ACCEPTED
+3d PAYOUT 5h 53m accepted from one shift, credited at $12, sent through Stripe with each segment itemized.Shift total: $70.60 · acceptance 97% PAID

Every station in the kitchen, and the bar and the counter too.

If it happens with your hands during a shift, it is probably on this list. If it is not, apply anyway and tell us.

01 / prepMOST WANTED
Prep and mise en place
Washing, peeling, dicing, portioning, breaking down whole birds and fish, stocks, sauces, and setting up a station.
02 / lineMOST WANTED
The line
Grill, flat-top, sauté, fry, and oven stations, calling and firing tickets, timing a table, plating and wiping for the pass.
03 / bakeCORE
Bakery and pastry
Mixing, shaping, scoring, and proofing dough, lamination, piping and decorating, loading and rotating ovens.
04 / drinksCORE
Coffee and bar
Dialing in and pulling shots, steaming and pouring milk, building cocktails, garnishing, and keeping a busy bar stocked.
05 / counterCORE
Fast food and counter service
Assembling burgers, bowls, and wraps to spec, running the fryer, wrapping and bagging orders at speed.
06 / dishCORE
Dish pit and close
Scraping, racking, running the machine, pots and sheet pans by hand, breaking down and sanitizing stations at close.

From application to payout in four steps.

STEP 01
Apply below
Your station, your city, how many hours a week you might record, and a few sentences on a typical shift. A person replies within one business day.
STEP 02
Restaurant agreement and setup
We get the owner's signature, agree what is off limits, then do a short call to check your camera and mount and go over when to pause.
STEP 03
Work the shift
Clip in at clock-in, cook as you always do, pause for breaks and family meal, and upload from your phone after close.
STEP 04
Review, note, Stripe
A reviewer watches the upload inside a few days and sends a note on what passed. Accepted hours are credited at $12 and paid out automatically.

How $12 an hour of footage adds up on a cook's schedule.

Prep POV image · 1200 × 900
Prep is the easiest footage to get accepted: steady light, a fixed board, and both hands in the shot.

Paid on accepted footage, never on hours worked

  • The rate — $12 for each hour a reviewer accepts. Expect 70 to 85 percent of what you send to pass once the mount is right.
  • A realistic week — record ten hours across three shifts, get eight accepted, earn $96. Record most of a 30-hour week and it is nearer $290.
  • Not a wage — your restaurant pays you as before. This is a licence fee for footage, under a short agreement with no exclusivity and no minimum.
  • Paid through Stripe — accepted hours land in your balance and pay out automatically, every upload itemized.
  • First hour guaranteed — your first genuine hour after onboarding is paid even if it fails review, with a note on what to change.
  • Your own gear — a phone or action camera on a chest mount. We check it on the call; we do not ship equipment.

Apply to the kitchen capture program.

Two minutes. A person on our data team reads it and replies within one business day with whether we can take you on now and what happens next.

Free to join · no quota · reply within one business day
[ received ]

Got it. We will be in touch.

A person on the eeko data team reads every application and replies within one business day with whether the kitchen program fits your station and what comes next. Nothing is recorded before onboarding and the restaurant's signature. You can also reach us at thomas@eeko.systems.

Kitchen AI training jobs: what cooks ask first.

How much do AI training jobs for cooks pay per hour?

$12 per accepted hour of footage, paid separately from your kitchen wages and tips. Accepted is the key word: breaks, smoke breaks, and the walk to the walk-in are paused out, and reviewers return roughly 15 to 30 percent of early uploads while cooks learn to keep the board in frame. A realistic first month is eight accepted hours a week, or $96. A cook who records most of a 30-hour week with a similar acceptance rate clears around $290. There is no cap and no required minimum.

Does the restaurant owner or manager need to agree?

Yes, in writing, before a single ticket is recorded. Kitchens are private workplaces, so we almost always enroll the restaurant rather than one cook, which means the whole line can record and you are not the person asking the chef for a favor. Coworkers who pass through the shot are blurred before anything is delivered. If you want us to make the approach to your owner or manager, say so in the form.

Will our recipes and menu end up in the footage?

Not unless the restaurant wants them to. The owner can rule specific dishes, stations, or prep off limits, and any printed recipe, prep sheet, or screen that lands in frame is blurred before delivery. Buyers are paying to see how a trained cook moves, cuts, flips, and plates, not for the spec on your house sauce. A kitchen that records only its routine prep and line work is giving AI teams exactly what they asked for.

Is this a second job or an hourly wage?

No. Your job, your schedule, and your pay stay with your employer. eeko pays you a separate per-hour licence fee for footage that passes review, under a short participation agreement with no exclusivity and no quota. Record every shift or one shift a month; stop whenever you like. Hours you do not record and uploads that do not pass are not paid, apart from your first hour, which is paid regardless.

What camera works in a hot, wet, busy kitchen?

Your own phone in a chest harness or a small action camera on a chest mount, which handles steam, splashes, and heat better than most people expect. We do not supply equipment, but we confirm on the onboarding call that what you own will work and show you the mount height that keeps the cutting board and the pan in frame while your hands stay free. Hood lighting is usually plenty.

What does a reviewer count as an accepted hour?

Footage a person on our team has watched and can use: it shows real kitchen work from your own eye line, it is sharp and lit well enough to follow the knife and the pan, the restaurant had agreed to recording in writing, and it is not a repeat of something you sent before. You get a note on every upload saying what passed and what to fix, so acceptance rates climb quickly after the first week.

Who gets the footage from my shift?

Named robotics and AI organizations that have signed a written licence with eeko, who use it to train and evaluate systems that must learn how food gets prepped, cooked, plated, and cleared away. Faces, screens, and paperwork are removed first, and every clip carries its consent record, a cryptographic fingerprint, and a signed provenance record. Nothing is posted publicly or sold through an open marketplace, and our verified human data page documents the whole chain.

Own or run a kitchen? Put the whole line on it.

Restaurants, bakeries, cafés, and caterers join under one agreement. You decide what is off limits, every cook who records is paid for their own accepted hours, and we handle consent and blurring so nobody on your team has to think about it during service. Mention the size of your kitchen in the form.

Pastry POV image · 800 × 1000
Pastry — dough that fights back, folded by someone who knows when it is ready.
Barista POV image · 800 × 1000
Coffee — steam, pitcher, pour, in a rhythm a machine has to learn by watching.
Dish pit POV image · 800 × 1000
Dish pit — scrape, rack, run, stack. Hard for a robot, routine for you.

Experienced within

  • SOC 2 Type II
  • ISO 27001
  • HIPAA
  • HITRUST r2
  • ISO 27701
  • PCI DSS
  • NIST CSF 2.0
  • CMMC
  • FedRAMP
  • GDPR

Markets served.

As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets:

New York City, New York (NY)

Los Angeles, California (CA)

Chicago, Illinois (IL)

Houston, Texas (TX)

Phoenix, Arizona (AZ)

Philadelphia, Pennsylvania (PA)

San Antonio, Texas (TX)

San Diego, California (CA)

Dallas, Texas (TX)

San Jose, California (CA)

Austin, Texas (TX)

Jacksonville, Florida (FL)

Fort Worth, Texas (TX)

Columbus, Ohio (OH)

Charlotte, North Carolina (NC)

Indianapolis, Indiana (IN)

San Francisco, California (CA)

Seattle, Washington (WA)

Denver, Colorado (CO)

Washington, District of Columbia (DC)

Boston, Massachusetts (MA)

El Paso, Texas (TX)

Nashville, Tennessee (TN)

Detroit, Michigan (MI)

Oklahoma City, Oklahoma (OK)

Portland, Oregon (OR)

Las Vegas, Nevada (NV)

Memphis, Tennessee (TN)

Louisville, Kentucky (KY)

Baltimore, Maryland (MD)

Milwaukee, Wisconsin (WI)

Albuquerque, New Mexico (NM)

Tucson, Arizona (AZ)

Fresno, California (CA)

Sacramento, California (CA)

Kansas City, Missouri (MO)

Atlanta, Georgia (GA)

Miami, Florida (FL)

Colorado Springs, Colorado (CO)

Raleigh, North Carolina (NC)

Omaha, Nebraska (NE)

Long Beach, California (CA)

Virginia Beach, Virginia (VA)

Oakland, California (CA)

Minneapolis, Minnesota (MN)

Tulsa, Oklahoma (OK)

Arlington, Texas (TX)

New Orleans, Louisiana (LA)

Wichita, Kansas (KS)

Cleveland, Ohio (OH)

Tampa, Florida (FL)

Bakersfield, California (CA)

Aurora, Colorado (CO)

Honolulu, Hawaii (HI)

Anaheim, California (CA)

Santa Ana, California (CA)

Corpus Christi, Texas (TX)

Riverside, California (CA)

Lexington, Kentucky (KY)

St. Louis, Missouri (MO)

Stockton, California (CA)

Pittsburgh, Pennsylvania (PA)

Saint Paul, Minnesota (MN)

Cincinnati, Ohio (OH)

Greensboro, North Carolina (NC)

Anchorage, Alaska (AK)

Plano, Texas (TX)

Lincoln, Nebraska (NE)

Orlando, Florida (FL)

Irvine, California (CA)

Newark, New Jersey (NJ)

Toledo, Ohio (OH)

Durham, North Carolina (NC)

Chula Vista, California (CA)

Fort Wayne, Indiana (IN)

Jersey City, New Jersey (NJ)

St. Petersburg, Florida (FL)

Laredo, Texas (TX)

Madison, Wisconsin (WI)

Chandler, Arizona (AZ)

Buffalo, New York (NY)

Lubbock, Texas (TX)

Scottsdale, Arizona (AZ)

Reno, Nevada (NV)

Glendale, Arizona (AZ)

Gilbert, Arizona (AZ)

Winston-Salem, North Carolina (NC)

North Las Vegas, Nevada (NV)

Norfolk, Virginia (VA)

Chesapeake, Virginia (VA)

Fremont, California (CA)

Garland, Texas (TX)

Richmond, Virginia (VA)

Baton Rouge, Louisiana (LA)

Boise, Idaho (ID)

San Bernardino, California (CA)

Spokane, Washington (WA)

Des Moines, Iowa (IA)

Modesto, California (CA)

Birmingham, Alabama (AL)

Tacoma, Washington (WA)

Fontana, California (CA)

Oxnard, California (CA)

Fayetteville, North Carolina (NC)

Huntsville, Alabama (AL)

Moreno Valley, California (CA)

Rochester, New York (NY)

Glendale, California (CA)

Yonkers, New York (NY)

Augusta, Georgia (GA)

Amarillo, Texas (TX)

Little Rock, Arkansas (AR)

Akron, Ohio (OH)

Shreveport, Louisiana (LA)

Grand Rapids, Michigan (MI)

Mobile, Alabama (AL)

Salt Lake City, Utah (UT)

Huntsville, Texas (TX)

Tallahassee, Florida (FL)

Overland Park, Kansas (KS)

Knoxville, Tennessee (TN)

Worcester, Massachusetts (MA)

Brownsville, Texas (TX)

New Port Richey, Florida (FL)

Jackson, Mississippi (MS)

Providence, Rhode Island (RI)

Fort Lauderdale, Florida (FL)

Sioux Falls, South Dakota (SD)

Tempe, Arizona (AZ)

Cape Coral, Florida (FL)

Springfield, Missouri (MO)

Pembroke Pines, Florida (FL)

Eugene, Oregon (OR)

Peoria, Arizona (AZ)

Corona, California (CA)

Lancaster, California (CA)

Rockford, Illinois (IL)

Salinas, California (CA)

Palmdale, California (CA)

Springfield, Massachusetts (MA)

Charleston, South Carolina (SC)

Duluth, Minnesota (MN)

London, England (ENG)

Dublin, Ireland (IRE)