AI Scoring and Evaluations Architect

Position: AI Scoring and Evaluations Architect

Location: Ludhiana · 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

Education:

• 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.
• Strong 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.