Machine Learning Engineer
Resume:
Venu Madhav Vema
**** ********* **, *******, ***** 77054
346-***-**** # ************@*****.*** ï LinkedIn § GitHub Summary
Experienced MLOps Engineer adept at orchestrating pipelines, deploying environments, and implementing monitoring tools. Proficient in TensorFlow and skilled in fine-tuning ML models for diverse tasks, including NLP using Transformer architectures like GPT. Experienced in Lang chain for NLP. Committed to collaborative learning and contributing to generative AI projects.
Education
University of Houston January 2022 – December 2023 Master in DataScience Engineering Houston, Texas
JB Institute of Engineering and Technology Augest 2017 – May 2021 Bachelor of Technology in Electrical and Electronics Engineering Hyderabad, India Technical Skills
Languages: Python, R, SQL, C, C++, JavaScript, HTML. Tools: AWS Sage Maker, Hive, Amazon Sage Maker Studios, Visual Studio Code, Docker, Power-BI, Tableau Desktop, Git-Hub, MYSQL, Anaconda, MS-Excel, MS-Power Point, Mat-Lab, Visual Base Application, Apache Spark. Analytical Skills: Strong Analytical and Problem-solving skills, Data Cleaning and Mining, Exploratory of Data Analysis, Time Series Analysis, Marketing Analytics, Creating the pipelines (CI/CD), Model Building. Work Experience
Infosys May 2020 – November 2021
Machine Learning Engineer Hyderabad, India
• Developed and maintained automation scripts and tools for various tasks using terraform, Jenkins pipeline scripts.
• Implemented in Machine learning operation lifecycle, which included data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
• Deployed machine learning models to AWS Sage Maker endpoints, utilizing a range of deployment configurations for real-time processing, batch processing and managing the entire machine learning life cycle
• Hands-on experience in using Terra form to efficiently create and provision AWS resources,including instances, S3 buckets, and various other cloud resources. This expertise allows for streamlined and reliable resource deployment within AWS infrastructure.
• Deployed machine learning models to AWS Sage Maker endpoints, utilizing a range of deployment configurations for real-time processing, batch processing and managing the entire 5. machine learning life cycle
• pipelines for deploying machine learning models and workflows. data processing workflows and scheduled ETL jobs. Tech AI Sep 2023 – March 2024
Senior Machine Learning Engineer Texas, USA
• Developed interactive web application using Streamlit for chat-based interaction with multiple PDF files.
• Integrated PyPDF2 for content extraction and langchain/FAISS for text processing.
• Utilized Google Generative AI for language modeling, including question answering and conversation generation.
• Demonstrated problem-solving skills in handling PDF file complexities and optimizing application performance
• Implemented text splitting, vectorisation, and similarity search with langchain and FAISS.
• Experienced in Lang chain for natural language generation and understanding, proficient in GAN’s for image synthesis, and skilled in managing vector databases and utilizing embedding for efficient data representation.
• Experienced in utilizing Bedrock, an open-source platform, to monitor and validate machine learning models in production. Proficient in setting up automated workflows with Bedrock for model validation and governance, ensuring optimal performance and compliance with regulatory standards
• Implemented in Machine learning operation life cycle, which included data pre-processing, feature engineering, model training, validation, deployment, and monitoring.
• Crafted Terra form and containerisation scripts with a high level of expertise and precision and bridged the gap between data science and infrastructure by creating efficient and automated pipelines for deploying machine learning models and workflows.
• Developed and maintained automation scripts and tools for various tasks using Terra form, Jenkins pipeline scripts.
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