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Aaditey Pillai

Intern AI/ML Engineer specializing in LLM applications, RAG, and model evaluation

Atlanta, GAAI Engineer Intern1 years experienceInternArtificial IntelligenceTechnologySaaS
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About

Backend/ML engineer who built production LLM-enabled systems at PRGX, including an interpretable contract opportunity scoring engine (Bradley-Terry pairwise ranking) that reached 0.82 weighted Spearman agreement with SME auditors and was integrated into workflow. Also built a Duke student advisor chatbot and hardened it for real-world reliability/security with schema-driven tool calling, normalization, and off-domain defenses; led staged production rollouts with shadow testing and achieved 0.90 F1 on a new extraction field before shipping.

Experience

AI Engineer InternPRGX Global
Machine Learning InternCelusion Technologies

Education

Duke Universitymaster, Artificial Intelligence (2026)
SRM Institute of Science and Technologybachelor, Electronics & Communications Engineering (2023)

Key Strengths

  • Designed and shipped an LLM-assisted contract opportunity scoring engine integrated into auditor workflows
  • Strong focus on interpretability in ML systems (Bradley-Terry pairwise ranking over deep models)
  • Achieved 0.82 weighted Spearman correlation vs SME contract rankings
  • API reliability patterns for LLM products (schema-enforced tool inputs, normalization, consistent response shapes, clarifying-question fallback)
  • Led production pipeline migration with shadow-mode testing and staged rollout
  • Delivered 0.90 F1 contract-number extraction before shipping to production
  • Security-minded backend design (JWT auth, RBAC, tenant-scoped queries, abuse prevention, AI guardrails)
  • Proactively identified conversational jailbreak/off-domain failure modes and hardened the system (re-grounding, confidence checks, tool restrictions)

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Languages

English

Skills

PythonPandasNumPyScikit-LearnObject-Oriented Programming (OOP)DataclassesFeature SelectionDuplicate Removal (Deduplication)Feature EngineeringEnsemble LearningVoting ClassifierRandom ForestGradient BoostingLogistic RegressionBradley–Terry Model