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\begin{document}

\begin{center}
    \textbf{\Large SAI NIHAR REDDY PALEM} \\
    \small\href{mailto:[email protected]}{[email protected]} $\mid$ (562)-822-7482 $\mid$ San Jose, CA $\mid$ 
    \href{https://github.com/niharpalem}{GitHub} $\mid$ \href{https://www.linkedin.com/in/nihar-palem-1b955a183/}{LinkedIn} $\mid$ \href{https://nihar-palem.medium.com/}{Medium} $\mid$ \href{https://huggingface.co/spaces/Niharmahesh/Portfolio}{Portfolio}
\end{center}

\resumeSection{Summary}
{\small As an AI engineer with a strong foundation in machine learning and data engineering, I specialize in developing robust data pipelines, implementing efficient annotation systems, and creating comprehensive evaluation metrics to enhance AI model performance. My experience spans from large-scale data processing to cutting-edge model development using technologies like PyTorch and TensorFlow. I thrive in collaborative, fast-paced environments where I can apply my problem-solving skills to drive innovative AI solutions. With a passion for advancing AI in creative domains, I am dedicated to pushing the boundaries of what's possible in AI-assisted design and making these tools accessible to all users.}

\resumeSection{Education}
{\small
\textbf{San Jose State University, California, USA} \hfill \textit{Jan 2023 -- Dec 2024}\\
\textit{Master of Science, Data Analytics}\\
\small{Relevant Coursework: Machine Learning, Deep Learning, Big Data Analytics, Mathematics for Data analysis}

\textbf{Sreenidhi Institute of Science and Technology, Hyderabad, India} \hfill \textit{June 2015 -- June 2019}\\
\textit{Bachelor of Technology, Electrical and Electronics Engineering (EEE)}
}

\resumeSection{Technical Skills}
{\small
\begin{itemize}[itemsep=0pt, leftmargin=*]
    \item \textbf{AI/ML Infrastructure:} PyTorch, TensorFlow, Scikit-Learn, Apache Spark, Docker, Model Development Pipelines
    \item \textbf{Machine Learning:} Deep Learning, Computer Vision, NLP, Reinforcement Learning, Vision Transformers, LLMs (GPT, LLaMA)
    \item \textbf{Data Engineering:} ETL/ELT Pipelines, Apache Airflow, Data Annotation Systems, CRISP-DM methodology
    \item \textbf{Cloud \& Big Data:} AWS (Certified), GCP (BigQuery, Cloud Composer, Cloud Storage), Snowflake, AWS Redshift
    \item \textbf{Data Visualization:} Tableau, PowerBI, Seaborn, Matplotlib, Streamlit
    \item \textbf{Databases:} MySQL, MongoDB, Snowflake, BigQuery
    \item \textbf{Programming Languages:} Python (Advanced), SQL (Advanced)
\end{itemize}
}


\resumeSection{Professional Experience}
{\small
\textbf{San Jose State University, San Jose} \hfill \textit{Aug 2024 -- Dec 2024}\\
\textit{Instructional Student Assistant}
\begin{itemize}[itemsep=0pt, leftmargin=*]
    \item Improved student project implementation efficiency by 30\% through comprehensive feedback and technical guidance.
    \item Reviewed and debugged student data pipelines, offering solutions for complex technical challenges in data analysis and ML model optimization.
\end{itemize}

\textbf{Bharat Electronics Limited, Hyderabad} \hfill \textit{Feb 2021 -- Mar 2022}\\
\textit{Data Analyst}
\begin{itemize}[itemsep=0pt, leftmargin=*]
    \item Optimized SQL queries for multi-million row defense databases, improving analysis efficiency by 40\% across Navy, Air Force, and international defense project analytics.
    \item Developed and maintained 100+ Power BI dashboards tracking defense electronics sales, production costs, and project metrics, enabling data-driven decisions for senior management.
    \item Implemented data standardization protocols using SQL triggers, ensuring consistency in currency conversions and text formatting.
\end{itemize}
}

\resumeSection{Projects and Achievements}
{\small
\textbf{Multi-Agent Job Search System} \href{https://huggingface.co/spaces/Niharmahesh/Multi_Agent_Job_search_and_match}{\textcolor{gray}{Application}} 
\hfill \textit{Jan 2025}
\begin{itemize}[itemsep=0pt, leftmargin=*]
    \item Engineered dual-agent platform using LLaMA models (8B for parameter extraction and resume summarization, 70B for matching), implementing real-time web scraping across LinkedIn, Glassdoor, and Indeed with automated batch processing of 60+ jobs per search.
    \item Developed intelligent matching system with resume summarization and job compatibility scoring, achieving 70\% reduction in search time through optimized prompt engineering and structured data processing.
\end{itemize}

\textbf{Job Easz Data Collector} 
\href{https://huggingface.co/spaces/Niharmahesh/job_easz}{\textcolor{gray}{Application}} 
\hfill \textit{Dec 2024}
    \begin{itemize}[itemsep=0pt, leftmargin=*]
        \item Developed an automated data collection pipeline using Apache Airflow, scraping 10000+ job postings daily from LinkedIn, Glassdoor, Indeed, and Google Jobs
        with a combination of roles and locations (1500+), storing data in Hugging Face datasets for open-source accessibility.
        \item Created an interactive dashboard featuring time series analysis of job postings and role-based trends, with search and filter functionalities.
        \item Enabled users to access and analyze job market data through an open-source application, promoting data-driven decision making in career planning.
    \end{itemize}

\textbf{Sign Language Assistant}
\href{https://huggingface.co/spaces/Niharmahesh/slr-easz}{\textcolor{gray}{Application}} 
\hfill \textit{Aug 2024 - Oct 2024}
    \begin{itemize}[itemsep=0pt, leftmargin=*]
        \item Built real-time ASL translation system using Google's Mediapipe Model and Random Forest classifier with optimized gesture recognition.
        \item Achieved 95\% accuracy for 19 alphabets while implementing interactive learning features with immediate feedback mechanisms.
    \end{itemize}

\textbf{National Infrastructure Monitoring} 
\href{https://huggingface.co/spaces/Niharmahesh/Data298}{\textcolor{gray}{Application}} 
\hfill \textit{Jan 2024 - Dec 2024}
    \begin{itemize}[itemsep=0pt, leftmargin=*]
        \item Developed Vision Transformer-based satellite imagery analysis system processing 40GB dataset with custom CV models for infrastructure monitoring.
        \item Achieved 85\% accuracy in change detection and deployed interactive temporal analysis interface on Hugging Face Spaces.
    \end{itemize}

\textbf{Stock Market Chatbot} 
\hfill \textit{Aug 2023 - Dec 2023}
    \begin{itemize}[itemsep=0pt, leftmargin=*]
        \item Created bilingual financial analysis chatbot integrating GPT-3.5 with yfinance API for real-time market insights and personalized recommendations.
        \item Engineered high-performance backend using Apache Spark and Snowflake, achieving 30\% query optimization with sub-5 second response time.
    \end{itemize}

\textbf{Twitter Trend Analysis with BigQuery} \hfill \textit{Jan 2023 - Apr 2023}
    \begin{itemize}[itemsep=0pt, leftmargin=*]
        \item Engineered GCP-based data pipeline using Cloud Composer and BigQuery, implementing OLAP analytics with Star Schema for processing 10k daily tweets.
        \item Developed automated ETL workflows with custom Python operators for data transformation, achieving 40\% improvement in processing efficiency.
    \end{itemize}
}

\resumeSection{Certifications}
{\small
\begin{itemize}[itemsep=0pt, leftmargin=*]
    \item \textbf{AWS Certified Cloud Practitioner:} Validated knowledge of AWS services, security, and architectural principles (Jan 2024).
\end{itemize}
}

\end{document}