AI Scoring and Evaluations Architect

- AI scoring architectures
- Rubric-to-scoring logic
- Scoring prompts and evaluation frameworks
- Speech, acoustic and language-analysis pipelines
- Natural language processing and machine-learning components
- Psychometric scoring and calibration logic
- Benchmark, annotation and calibration datasets
- Human-rated reference datasets
- Model accuracy, consistency and error-analysis reports
- Bias, edge-case and failure-mode analyses
- Regression-testing frameworks
- Scoring and feedback API specifications
- Scoring-model documentation and version records

Ideal experience

Highly capable research-oriented candidate with 3–5 years.

Relevant experience could include:

- Speech recognition or speech analytics
- NLP evaluation
- Machine-learning model validation
- Automated essay or response evaluation
- LLM evaluation systems
- Acoustic or phonetic analysis
- Recommendation or classification systems

· M.Tech., M.S. or Ph.D. in Artificial Intelligence, Machine Learning,



Data Science, Computer Science, Computational Linguistics, Natural Language Processing or a closely related field.

· M.Tech., M.S. or Ph.D. in Signal Processing, Electronics and Communication Engineering, Speech Technology or Audio Processing, with demonstrated experience in speech recognition, acoustic analysis, phonetics or spoken-language evaluation.

· Postgraduate or doctoral research experience in Computational Linguistics or Natural Language Processing, with substantial work in language-model evaluation, automated scoring, text analytics, human annotation or linguistic feature extraction.

· Robust applied AI researchers or machine-learning engineers with proven experience in speech, language, evaluation systems or assessment technology, even where their formal degree is in another quantitative discipline.

📌 AI Scoring and Evaluations Architect (Ludhiana)
🏢 TCY Learning Solutions (P
📍 Ludhiana