Associate Engineer in ML

Shashank Uppalamurthy

Phone: 614-***-**** Email: **********@*****.***

SUMMARY

Recent graduate with 1+ years of experience in machine learning and data engineering. Seeking opportunities in AI/ML to leverage my skills and implement innovative approaches. Proficient in developing scalable ML models, data pipelines, and deriving actionable insights from large datasets. Passionate about solving complex challenges and driving impactful solutions through advanced analytics and AI technologies. My goal is to contribute to the organization’s success while advancing my career in data and cloud technologies.

EDUCATION

Master of Science in Computer Science, Kent State University Aug 2023 – Dec 2024 Bachelor of Engineering in Computer Science Engineering, Anna University Aug 2019 – May 2023 TECHNICAL SKILLS

Programming Languages: SQL, Python, Shell Scripting, JavaScript Packages: PyTorch, Pandas, Scikit-learn, NLTK, Flask TensorFlow, Matplotlib, Seaborn, NumPy, Google Colab, Jupyter Database Technologies: MySQL, PostgreSQL, Oracle, SQL Server, Aurora, Snowflake Cloud Services: S3, Redshift, Glue, CloudWatch, Sage maker, Machine Learning, EMR, IAM, VPC, AutoML, Kubeflow Networking: TCP/IP, DNS, HTTP/s, Firewalls, LAN/WAN, Traceroute, CURL Tools, VMware Operating Systems: Windows, Linux, OS

AI Technologies: Random Forest, Streamlit Application, SVM, LLM, NLP CERTIFICATION AND COURSEWORK

Professional Machine Learning Engineer Google Cloud Google Cloud Data Analytics Google Cloud

Introduction to Artificial Intelligence and Machine Learning Coursera.com AWS Cloud Support Associate Coursera.com

Architecting with Google Compute Engine Coursera.com WORK EXPERIENCE

Associate Engineer Strategic Systems Inc Aug 2024 – Present

• Collecting, cleaning, and processing data to make it suitable for training ML models, including feature engineering and normalization.

• Working with senior engineers and data scientists to develop machine learning models tailored to specific use cases.

• Running experiments to train ML models, evaluating their performance using metrics such as accuracy, precision, and recall.

• Assisting in deploying models into production by containerizing them, integrating them with existing systems, and ensuring scalability.

• Monitoring deployed models for performance issues like data drift or concept drift and retraining them periodically with fresh data.

• Documenting the entire development process, including data sources, model architecture, training steps, and evaluation results for team reference and compliance.

• Collaborating with data scientists, software engineers, and business stakeholders to understand requirements, gather feedback, and improve solutions.

• Document key aspects of development, including data sources, model architecture, training processes, and evaluation results, for team knowledge sharing and compliance.

Machine Learning Engineer Pandata Group May 2024 – July 2024

• Developed and optimized real-time ML models using Python, TensorFlow, PyTorch, and Scikit-learn to solve complex business challenges with low-latency solutions

• Implemented data preprocessing pipelines using Pandas and NumPy, reducing data cleaning time by 99%.

• Troubleshooting memory and network issues in real-time Spark streaming jobs on AWS EMR clusters, ensuring efficient data processing and system stability

• Designed and optimized supervised and unsupervised learning algorithms to solve specific problems.

• Worked closely with cross-functional teams to design and implement AI-driven solutions, presenting insights through visualizations (using Matplotlib and Seaborn) to support data-driven decision-making.

• Built and fine-tuned machine learning models for predictive analytics, including regression, classification, and time series forecasting using algorithms like linear regression, random forests, and ARIMA. Associate Machine Learning Engineer Stratsol Systems Inc., Nov 2022 – June 2023

• Executed and optimized SQL queries within Jupyter Notebook to analyze data, generate insights, and streamline interactive workflows.

• Interact with Engineers, marketing team to understand product goals and data needs

• Implemented ETL pipelines to transform data and load it into Redshift, enabling efficient storage and organization of large-scale datasets

• Based on business use-case writing SQL scripts on on-prem data, encrypting data and giving cross account permissions on S3 bucket for business teams.

• Creating partitions on tables that contains historical data and controlling users access using Athena workgroups

• Tuning and troubleshoot Spark jobs on AWS EMR clusters, optimizing performance and ensuring efficient processing of large-scale datasets

• Contributed to natural language processing (NLP) tasks, including sentiment analysis and text classification, using tools like IDF and word embeddings to analyze financial documents PROJECTS

Show UP - Student Attendance Dashboard

For our capstone project, we developed a voice-based attendance system that accurately tracks student presence in different seating arrangements within the classroom. This system automates attendance, providing a more secure, efficient, and scalable solution for modern classrooms.

Kidney Creatine Analysis using probabilistic data management I developed a web application for Kidney Creatine Analysis that forecasts creatine level fluctuations based on patients' diets and helps determine kidney donation eligibility. For accuracy, I implemented a Markov Model for transitions and used a Random Forest Model to validate the results.

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