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Title Machine Learning Engineering Intern
Target Location US-MA-Worcester
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Candidate's Name
PHONE NUMBER AVAILABLE  EMAIL AVAILABLE  LinkedIn  PortfolioSKILLS Programming Languages: : Python, R, HTML, C/C++, JavaScript, CSS Softwares: Tableau, Atlassian, MySQL, Docker Hadoop, Hive, BitBucket Libraries and Frameworks: TensorFlow, PyTorch, Keras, PySpark, Sci-Kit Learn, Langchain Technologies: Generative AI, Git, Data Mining, Computer Vision, Fast API, Big Data Analysis, NLP EXPERIENCESS&C Intralinks Waltham, MAData Science Engineering Intern Oct 2023 - Dec 2023 Integrated Retrieval Augment Generation (RAG) pipelines into Conversational AI chatbot workflows using Hybrid search retrieval and vector databases, enhancing natural language processing capabilities. Engineered advanced prompt algorithms for diverse use cases like extraction from tables and NER, utilizing prompt engineering expertise, boosting data retrieval efficiency by 15% and improving accuracy by 10%. Revolutionized stakeholder interaction with NLP models through the creation of detailed Tableau dashboards, enhancing data comprehension by 2-folds and driving higher levels of collaboration. Keysight Technologies Calabasas, CAMachine Learning Intern May 2023 - Aug 2023 Assessed and deployed an efficient Virtual Assistant for ADS software, resulting in a 40% reduction in query response time. Introduced and stored diverse data formats (HTML, Text, PDF) into vector databases (FAISS, Lance) enabling retrieval speeds up to 3 times faster than traditional methods, using Langchain, RAG and semantic search. Fine-tuned an Open-Source Dolly model with 7 billion parameters using Parameter Efficient Fine-Tuning, providing a 0.7 ROUGE score in processing and responding to user queries accurately. Tieto Evry Pune, IndiaMachine Learning Engineer Aug 2021 - May 2022 Developed advanced ETL pipelines for moving healthcare data from transactional tables to Datamart, achieving a 35in data consistency and quality by meticulously managing outliers and null values. Performed a deep study on patient data using XGBoost and Random Forests in Python that helped in diagnosing diseases, increased the model performance by 13% and reduced manual classification by 56%. Deployed the model using FastAPI, integrated with Swagger for user-friendly testing. Implemented Docker to containerize the MLOps pipeline, facilitating seamless cross-team collaboration and creating consistent, reproducible environments for data extraction, model training, and deployment, resulting in a 30% reduction in deployment timeCERTIFICATIONSOracle Generative AI Certified Professional (Link) June 2024 PROJECTSMLOPS PIPELINE DOCKERIZATION ON HEALTHCARE DATA June 2024 Containerized a MLOps pipeline using Docker to ensure consistent environments and facilitate seamless integration across teams, incorporating data extraction from Amazon S3, model training using Scikit-learn and Flask for model deployment. FULL-STACK WEB-BASED QUESTIONNAIRE Jan 2024 Developed a full-stack questionnaire application using HTML, CSS, and JavaScript for the front end and MySQL for the backend, enhancing research efficiency at WPI.OLYMPICS DATA ANALYSIS USING PYSPARK Aug 2023 Incorporated PySpark for streamlined data analytics, transformative features, including sorting and visualizing total medals in each Olympics sport, showcasing PySparks prowess in efficient data processing and visualization. AMAZON CUSTOMER ANALYSIS Jan 2023 Implemented Extract, Transform, Load (ETL) processes on a dataset of 60,000 rows utilizing SQL to cleanse raw data, enhancing data quality and preparation, for advanced analytics using PowerBI Dashboards. EDUCATIONWorcester Polytechnic Institute Worcester, MAMaster of Science in Computer Science (GPA 3.6/4.0) Aug 2022 - May 2024 University of Mumbai Mumbai, IndiaBachelor of Engineering in Computer Engineering (GPA 3.6/4) Aug 2017 - Jun 2021

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