AI / ML Engineer
Production ML, model evaluation, data pipelines, APIs, and deployment.
For AI engineers
Your work should speak louder than your resume.
Build a living evidence profile around the systems you have shipped, the decisions you made, and the engineering standards you can demonstrate.
Your pathwayCandidate controlled
01
Upload your resume
Profile02
Attach project evidence
Evidence03
Run the agent benchmark
Proof04
Choose employer visibility
ConnectChoose your direction
Role-specific tracks, not one generic AI badge.
Generative AI Engineer
LLM applications, context design, structured outputs, guardrails, and evaluation.
RAG Engineer
Ingestion, retrieval, ranking, grounding, citation quality, and observability.
Agentic AI Engineer
Tool use, orchestration, state, recovery, human approval, and task evaluation.
AI Platform Engineer
Infrastructure, model gateways, reliability, security, cost, and developer experience.
More tracks over time
Tracks are versioned so the standard can evolve without rewriting past evaluation history.
Signal hierarchy
Every skill keeps its evidence label.
We never convert course attendance or a self-declared skill into a verified claim.
01
Self-reported
You have identified the skill; no independent evidence is attached yet.
02
Learning completed
Relevant learning activity is recorded, but completion is not verification.
03
Project demonstrated
A project you publish shows where and how you applied the skill; it is not independently verified.
04
Evaluation verified
A versioned scenario and structured review support the skill claim.
Project evidence
Show how you think, not only what you built.
A useful project record includes the problem, your role, architecture, engineering decisions, tradeoffs, tests, results, and known limitations.
Repository and README
Architecture and decisions
Evaluation and results
Risks and limitations
What approved employers may see
- Your candidate-approved identity and professional summary
- The source and level of each skill signal
- Candidate-published projects and active verification evidence
- Role fit, availability, and work preferences
- Development areas that provide honest context
Private reviewer notes, hidden checks, integrity details, and personal contact information are never public profile content.
Early access is open for profile building.