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