Mechanical engineering training data. Units carried, tolerances respected.
Worked problems, annotated drawings, parametric CAD, and design reviews produced by degreed mechanical engineers with design, analysis, and shop experience, then checked by a second engineer before delivery. For AI teams training or testing models that reason about physical things, and for engineers who want paid, remote work in their own discipline.
What is mechanical engineering training data?
Mechanical engineering training data is material an engineer would recognize as real work, packaged so a model can learn from it or be scored against it: a beam or heat-exchanger problem solved step by step with the units carried through; a drawing labeled with its dimensions, tolerances, GD&T callouts, and material; a parametric part with the design intent written down; a critique explaining why a bracket will crack at the fillet; a model's own solution marked step by step for where the physics went wrong.
Models trained on the public internet still lose a unit halfway through a calculation, propose parts no shop can machine or mold, misread a datum reference, skip the tolerance stack-up, and choose a material with no thought for fatigue or temperature. The textbook problem banks are already in every corpus, and the CAD libraries that get scraped carry licensing nobody can vouch for.
eeko builds AI for manufacturers and the engineering teams inside them, and the models we deploy need data that reflects how parts are actually designed and made. So we commission it: verified engineers build each item to your specification, a second engineer checks it blind, and the delivery carries a verifiable record for every part, drawing, and grade, the same verification stack used across the eeko data practice.
Three failures engineering models repeat, and the data that trains them out.
A general annotator can tell whether an answer looks finished. An engineer can tell whether the part would survive its first load cycle.
CAD datasets, drawing annotation, and engineering evaluation, to your spec.
The six requests we fill most often, each scoped by subdiscipline, difficulty, and volume, and each opened with a pilot batch.
- Tagged by subdiscipline and difficulty
- Independent second solve before acceptance
- Written new, never lifted from a textbook
- ASME Y14.5 and ISO GPS conventions
- Bounding boxes, fields, or structured JSON
- Agreement measured between annotators
- STEP, IGES, and native exports
- 3D shape fingerprint on every model
- Design intent recorded with the file
- DFM and DFA findings with severity
- Failure-mode reasoning in plain language
- Preference pairs between competing designs
- Rubric agreed in the pilot
- First-error index on every trace
- Reviewer agreement reported per batch
- Held out and timestamped
- Scored by engineers against written criteria
- Refreshed on a standing order
From brief to signed delivery, in four steps.
Agree the modeling and grading standard on a small batch, then run volume without re-arguing it.
The engineers behind the dataset, and what they hand over.
Who is on the eeko engineering network
- Mechanical design engineers — parts, mechanisms, and assemblies, with the CAD fluency to model them.
- Manufacturing engineers — machining, molding, sheet metal, and assembly judgment for DFM reviews.
- Thermal, fluids, and structural analysts — heat transfer, CFD, and FEA problem sets and simulation setups.
- CAD specialists and faculty — parametric modeling standards and graduate-level problem writing.
Delivered as CAD models, annotated drawings, problem sets, simulation setups, design reviews, and reasoning traces, in the formats your pipeline already reads.
Paid AI training work for mechanical engineers, on your own schedule.
Remote work that uses your actual discipline: write problems, annotate drawings, model parts, critique generated designs, and check a colleague's work. The rate is on the job before you accept it.
Identity, degree, and experience are confirmed once at onboarding. You then only see jobs whose requirements your verified profile meets.
- Degreed Mechanical engineering or a closely related discipline
- Experienced Several years in design, analysis, or manufacturing
- Advanced work A PE license, a graduate degree, or chartered status
- Tooling Fluent in a major CAD package and in GD&T
- Specialized Thermal systems, FEA, mechanisms, or tooling is a plus
Each job carries its scope, deadline, and rate. After the second engineer approves your item, the amount lands in your balance and Stripe pays it out automatically once we have confirmed who you are and your tax information.
- Write Problems solved in full, with units and assumptions written out
- Annotate Dimensions, tolerances, GD&T, and materials to a written guide
- Model and critique Build parts to a brief or review generated designs for buildability
- Review Another engineer's problems, drawings, or models as the second check
No minimum hours, no published byline, and nothing from your employer's vault: every job is new work or material you hold the rights to. How rates and review work across the program is on expert data annotation jobs.
Mechanical engineering training data questions.
What mechanical engineering training data can eeko produce?
Six things, mostly: problems with fully worked solutions in statics, dynamics, thermodynamics, heat transfer, fluids, machine design, and manufacturing; engineering drawings labeled for dimensions, tolerances, geometric tolerancing, and materials; parametric CAD parts and assemblies with design intent written down; design critiques for manufacturability and failure modes; step-by-step grades of a model's engineering reasoning; and prompt-and-reference sets for text-to-CAD evaluation. Each request is scoped by subdiscipline and difficulty and routed to engineers we have verified in that area.
Where do the CAD models in the dataset come from?
Two places, and both are documented. Either an engineer on the eeko network builds the part or assembly new, to your brief, or a creator who holds the rights licenses an existing model with consent recorded against that specific file. Every model gets a cryptographic fingerprint at intake, plus a 3D shape fingerprint so near-duplicate geometry is caught even when the file differs, and every one appears by hash on the signed delivery receipt. Nothing is pulled from public CAD libraries.
Do I need a PE license to do AI training work as a mechanical engineer?
Usually not. A mechanical engineering degree with real design, analysis, or manufacturing experience qualifies you for most of the work. A PE license, a graduate degree, or chartered status opens the advanced tasks, such as grading research-level reasoning or reviewing safety-critical designs. The requirements are printed on every job before you accept it, and we confirm identity and credentials once at onboarding rather than job by job.
How much does engineer-made training data cost?
It is priced per accepted item, and the price moves with the item type and the depth of review. A single annotated drawing is cheap; a parametric assembly with a documented design review is not. We quote a fixed price for a pilot batch after a short brief, so you see the standard and the unit economics before scaling, and the volume order is quoted the same way. A data lead replies inside one business day.
Can I take this work while holding a full-time engineering job?
Most engineers on the network do. Work is remote, each job states its scope, deadline, and rate before you take it, and there is no quota of hours. Two cautions: check your employer's outside-work and confidentiality rules first, and never bring your employer's drawings, models, or proprietary data into a job. Everything you make for eeko should be new work or your own licensed material.
Can we get exclusive rights to CAD and problem data?
Yes. Datasets commissioned through eeko can be licensed exclusively, with the scope, the term, and what exclusivity means for the contributing engineers all set out in writing before the first item is built. CAD exports come in STEP, IGES, or native formats, text and labels as JSON Lines, Parquet, or Croissant, and a standing order keeps new parts and problems arriving at the agreed standard.
Nearby solutions, industries, and fields.
Engineering data a shop would sign off on.
Tell us the subdisciplines, the volume, and the mistakes your model keeps making. A data lead replies inside one business day with a written spec and a fixed pilot price. Engineers: the application takes ten minutes.
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As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets: