The Exact ML Project I’d Build to Get Hired in 2026
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A framework for building ML portfolio projects that stand out to hiring managers. The key criteria are that a project should be personal, novel, relevant to target roles, and deployed live. The process involves starting from personal interests, generating questions those interests raise, filtering for ML-solvable problems, scoring ideas against feasibility and relevance, and deploying end-to-end using Python, Streamlit, GitHub Actions, and standard software engineering practices like unit tests and dependency management.
Table of contents
Why Most ML Projects FailExample ProjectStart With Your InterestsFilter Your Top PicksValidate The ProjectMake It LiveAnother Thing!Connect With Me210 Impressions