FreeCAD / Mechanical CAD Expert, AI Computer-Use Trainer

## About SME Careers
As AI systems become more sophisticated, they rely on human knowledge to better understand context and the world. At SME Careers, we partner with leading AI labs to improve how the next generation of intelligent systems learn, reason, and act. SME Careers is a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world's top AI companies and foundation model labs. Your expertise in parametric CAD will directly help improve the world's premier AI models.
## About the Role
AI agents are getting good at reading a screen and clicking through web forms. Put one in front of a parametric CAD package and it falls apart. FreeCAD is an unforgiving test case: multiple workbenches with overlapping capabilities, a constraint solver that fails in ways the interface doesn't explain, feature histories where the correct next action depends entirely on what was built twenty steps earlier, and the topological naming problem lying in wait for anyone who references geometry carelessly. Engineering intent lives in the model tree, not on the screen — and that is exactly what current agents cannot see.
In this remote, hourly contract role you will help close that gap. You will design realistic, challenging CAD tasks, then record yourself completing them on your own computer using recording tools we provide. Each recording captures the full picture of how expert work actually gets done, the sequence of actions, the interface state at every step, and the files before and after, and becomes both a demonstration the model learns from and a benchmark it is measured against.
Because a model can only learn from work that can be scored, an equally important part of the job is defining what "done correctly" means. Alongside each task you will write the objective and the steps you took, and specify how the result should be verified, what the finished part, sketch, assembly, or drawing has to satisfy for the outcome to count as correct, and which intermediate checkpoints a partially-successful attempt would hit. In CAD this is a sharper question than it looks: a part can be dimensionally correct and still be wrong, because the sketch is under-constrained, the feature order won't survive a parameter change, or the model references a face that will migrate the moment anything upstream is edited. Encoding that distinction, dimensionally right versus actually right, is the contribution we need from you.
This position is with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world's top AI companies and foundation model labs. Your work will directly help improve the world's premier AI models.
## What You'll Do
Author production-realistic CAD tasks: Write task briefs reflecting work an engineering team would actually assign, model a part to a dimensioned drawing, build a parametric family driven by a spreadsheet, assemble components with mating constraints, produce a TechDraw sheet with sections and tolerances, prepare geometry for manufacture or export, scoped tightly enough that the outcome can be objectively verified.
- Record expert demonstrations: Set up your own environment for the task (reference drawings, source files, workbenches and add-ons in place) and record yourself executing it end to end with the provided capture tooling, producing a complete trace of actions, interface state, and file changes.-
Document the workflow step by step: Log the steps you took in a form another engineer could follow and reproduce, in clear professional English.
Define verification and success criteria: Specify what the finished model must satisfy, dimensional correctness, fully-constrained sketches, robust feature references, a tree that survives a parameter change, plus the intermediate milestones that mark real progress and the plausible wrong paths that should not be credited.
Cover the range of difficulty: Produce tasks from single sketch-and-pad operations up to long, multi-step workflows that cross applications (a drawing opened from a PDF, dimensions pulled from a spreadsheet, output handed to a slicer, mesh or STEP data round-tripped from another tool).
Review and quality-check others' work: For those who move into QA, audit submitted traces for task realism, recording completeness, step-to-action mapping, and whether the stated success criteria genuinely hold for the model produced.
Work to project quality standards: Keep recordings free of personal information and confidential client geometry, use only approved applications, and complete all work using your own expertise, the use of closed-source AI assistants is contractually prohibited on this project.
## What You Bring
2–5 years of professional experience in mechanical design, product development, manufacturing engineering, or a comparable CAD-centric role (contract, studio, in-house, or freelance).
Genuine FreeCAD proficiency, not just general CAD experience. You work fluently in Sketcher and Part Design, understand the difference between the Part and Part Design approaches and when each is appropriate, and can build a model whose feature tree is robust rather than merely correct on the first render.
Solid parametric modeling fundamentals: fully-constrained sketching, datum planes and local coordinate systems, expressions and spreadsheet-driven parameters, and an understanding of how topological naming affects downstream references.
Practical troubleshooting instincts — you can diagnose a failing constraint solver, an over-constrained sketch, a broken feature reference after an upstream edit, and a boolean that fails on non-manifold or self-intersecting geometry.
Working knowledge of at least two more FreeCAD workbenches relevant to real workflows (Assembly, TechDraw, Draft, Spreadsheet, FEM, or CAM/Path).
File-format fluency: STEP, IGES, BREP, STL/mesh, and the practical consequences of moving between solid and mesh representations.
A computer you can install our recording tools on and work in daily: Windows 11, Ubuntu (X11), or macOS. Batches are assigned by operating system, and hardware capable of running FreeCAD comfortably alongside a screen recorder is required.
Comfort being screen-recorded while you work, and the discipline to keep personal information and any client-confidential geometry out of frame.
English proficiency: minimum B2, with the written clarity to document a workflow another engineer can reproduce.
Ability to apply detailed rubrics consistently and make repeatable quality judgments across many similar tasks.
Highly detail-oriented and self-directed, with strong asynchronous work habits for remote, flexible-hour contract work.
Key Responsibilities
Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.

Work arrangement
Yes