Senior Machine Learning Engineer, Text-To-Speech (Remote/France) Application Experience: Negative (but the role/mission is exciting) Outcome: Rejected after Pre-Assessment Review: The company's mission in Voice AI is genuinely exciting, and the role itself (owning the end-to-end TTS stack) is highly appealing. However, the initial pre-assessment phase is poorly designed and misleadingly described. The recruiter email stated the assessment would test "hands-on coding proficiency." In reality, the test was highly inconsistent and covered a vast, unfocused range of topics. It was a mixture of: 1. Obscure/Basic Theory: Many questions involved university-level theory (e.g., specific definitions in linear algebra or obscure ML terms) that are irrelevant for a Senior Engineer focused on model design and production deployment. 2. Tricky/Unclear Questions: A significant number of items were ambiguously worded, overly complex, or designed to trick the candidate rather than test deep, practical understanding. 3. Advanced Python Coding: The coding component was indeed challenging and appropriate for a senior role, but its effectiveness was diminished by the unnecessary theoretical noise. This process fails to accurately screen senior candidates and penalizes those who focus their preparation on modern, practical, production-oriented skills (which the job description claims to require). The assessment needs to be completely re-scoped to reflect the actual demands of a Senior ML position at SoundHound.