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SAI S. — AI Engineer from India

SAI S.

AI Engineer

India Less than 1 year
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About

Sai S., an accomplished AI Engineer based in Hyderabad, India, excels in the development and deployment of machine learning and deep learning models. With a robust proficiency in Python, TensorFlow, PyTorch, and scikit-learn, Sai has successfully implemented AI solutions across diverse domains, from computer vision and NLP to generative AI and predictive analytics. Currently at Zensar Technologies, Sai plays a key role in end-to-end data modeling and model training for NVIDIA's LLM systems, focusing on enhancing AI-generated code and reasoning through RLHF. Previous internships include designing computer vision pipelines for DRDO, utilizing IBM Cloud for predictive ML models, and unifying enterprise data at NMDC. Sai's technical skill set is complemented by a strong foundation in SQL, TensorFlow, and cloud services like GCP, IBM Cloud, and AWS. With a B.Tech in Computer Science & Engineering (AI & ML) from GITAM, Sai continues to contribute to AI innovation, such as the development of a multi-fusion transformer for video captioning, which demonstrates expertise in GenAI.

Experience

  • AI Prompt Engineer

    Zensar Technologies (Client: NVIDIA) · 2026 — Present
    Managed the complete data modeling, dataset curation, and model training workflows for advanced LLM and reasoning systems utilized by NVIDIA research and product teams. Evaluated and ranked AI-generated code along with reasoning traces, identifying failure modes and transforming them into effective RLHF/preference data to enhance model performance. Worked collaboratively with NVIDIA research and product stakeholders to clarify ambiguous requirements into prompt suites, evaluation rubrics, and dataset specifications.

  • AI Intern

    Defence Electronics Research Laboratory (DRDO) · 2024 — 2024
    Designed and implemented a production-ready computer vision pipeline for face recognition using Python and OpenCV, achieving a proof of concept for automated monitoring with 98% recognition accuracy. Executed the full machine learning workflow, including data collection, preprocessing, model training, evaluation, and integration with backend services and secure databases. Enhanced the reliability and robustness of inference and evaluation routines for real-time image-processing applications.

  • AI Intern

    IBM SkillsBuild · 2024 — 2024
    Created predictive machine learning models in Python using structured datasets, focusing on feature engineering, statistical modeling, and thorough evaluation across various methods such as classification, regression, and ensemble techniques. Utilized IBM Cloud, Watson Studio, and Watson ML to achieve comprehensive AI workflows that produced actionable forecasting and decision-support insights.

  • AI Intern

    NMDC · 2024 — 2024
    Developed SQL data models and REST API backend services to consolidate fragmented enterprise employee data for downstream analytics and machine learning applications. Conducted extensive data cleaning, transformation, and validation efforts to enhance data consistency and readiness for analysis. Facilitated automated reporting processes that minimized manual processing time while increasing operational visibility for leadership.

  • AI Intern

    Google for Developers (ML Program Track) · 2024 — 2024
    Constructed deep learning models (CNNs) for image-based recognition, executing controlled experiments across extensive image and text datasets. Implemented Python-driven machine learning workflows for comprehensive data preparation, model experimentation, evaluation, and iterative enhancement.