Aravind Kumar Email & Phone Number

Chicago, Il, Us

Led the development and fine-tuning of LLMs, enhancing model accuracy for customer support automation and personalized content generation.Developed and implemented AI/ML solutions in healthcare to enhance predictive analytics, patient outcomes, and operational efficiencyApplied Python programming skills to build and deploy machine learning models using TensorFlow, PyTorch, and sci-kit-learn, resulting in mention specific outcomes, e.g., improved accuracy, and reduced processing time.Conducted data cleaning, preprocessing, and feature engineering on large datasets using Databricks, enhancing data quality and model performance in Azure cloud environments.Implemented generative AI Gen AI models to create dynamic content, improving marketing campaign efficiency and reducing manual effort.Developed and deployed sophisticated conversational Gen AI agents using Google Vertex AI Agent Builder, ensuring seamless integration with existing applications and systems.Developed and trained machine learning models using Azure ML, utilizing its built-in algorithms and automated machine learning capabilities to enhance model accuracy and efficiency.Integrated Azure AI Search into applications to enable advanced search capabilities and contextual querying, enhancing the retrieval of relevant information from large datasets.

Florida, United States

Design and implement predictive models using techniques such as logistic regression, linear regression, and neural networks.Collaborate with ML Engineers and Data Scientists to build data and model pipelines and help in running machine learning tests and experimentsExperience with Statistical Modeling, Data Extraction, Data cleaning, Data screening, Data Exploration, and Data Visualization of structured and unstructured datasetsAbility to implement large-scale Deep Learning and Machine Learning algorithms to deliver resourceful insights and inferencesManaged model registries and versioning for LLMs, ensuring consistent and reproducible deployments across development and production environments.Utilized XGBoost for high-performance predictive modeling, achieving significant improvements in accuracy and efficiency through advanced gradient boosting techniques.Created and managed end-to-end ML pipelines in Azure ML, streamlining model training, evaluation, and deployment.Utilized LLM APIs for integrating language understanding capabilities into applications, enhancing user interaction with advanced conversational AI features.Implemented and optimized enterprise search solutions using Azure AI Search to enhance data accessibility and user experience.Build and deploy machine learning models including Latent Class Analysis (LCA), Random Forest, and neural networks to solve complex business problems.Using machine learning techniques supervised, unsupervised, reinforcement learning as applied to the travel, transport, or logistics industryPerform statistical tests including t-tests and other statistical techniques to analyze data and derive meaningful insights.Conducted various evaluations of LLMs to assess their effectiveness in handling complex language tasks, ensuring high-quality outputs, and identifying areas for model improvement.Apply segmentation and clustering techniques to categorize data into meaningful groups and target specific business needs.

Mumbai, Maharashtra, India

Worked with several R packages including knit, dplyr, Spark, R, Causal Infer, and Space-Time.Coded R functions to interface with Caffe Deep Learning Framework.Analyzed large healthcare datasets to identify trends and patterns, supporting data-driven decision-making for clinical and administrative teams.Used Pandas, NumPy, Seaborn, SciPy, Matplotlib, Scikit-learn, and NLTK in Python for developing various machine learning algorithms.Installed and used Caffe NLP Framework.Managed Docker images using AWS ECR to ensure secure and scalable deployment on AWS.Worked on different data formats such as JSON, and XML and performed machine learning algorithms in Python.Set up storage and data analysis tools in Amazon Web Services cloud computing infrastructure.Implemented end-to-end systems for Data Analytics and Data Automation and integrated with custom visualization tools using R, Mahout, Hadoop, and MongoDB.Developed MapReduce/Spark Python modules for machine learning & predictive analytics in Hadoop on AWS. Implemented a Python-based distributed random forest via Python streaming.Automated model training and deployment workflows using the SageMaker SDK for efficient MLOps.Utilized Spark, Scala, Hadoop, HBase, Cassandra, MongoDB, Kafka, Spark Streaming, MLLib, Python, and a broad variety of machine learning methods including classifications, regressions, dimensionally reduction, etc and utilized the engine to increase user lifetime by 45% and triple user conversations for target categories.Used Spark Data frames, Spark-SQL, and Spark MLLib extensively and developed and designed POCs using Scala, Spark SQL, and MLlib libraries.

Hyderabad, Telangana, India

Designed and implemented scalable Java-based applications, contributing significantly to the team's deliverables and product evolution.Led the transition from a monolithic, batch-based system to a modern, cloud-based microservice architecture, enhancing system reliability and performance.Collaborated closely with business partners to thoroughly understand business requirements, ensuring the successful delivery of new user stories and features.Spearheaded automation initiatives across the software development lifecycle, significantly reducing time-to-market and improving operational efficiency.Employed an extreme automation mindset, applying CI/CD principles using Jenkins and GitHub Actions to streamline build and deployment processes.Contributed to the design and implementation of front-end components using Angular, improving user experience and interface responsiveness.Developed and maintained high-quality, secure, and efficient software solutions using Java and Spring Framework, meeting critical business requirements.Engaged in the full product development cycle, from analysis and design to programming, testing, and deployment, ensuring high reliability and operations standards.Actively participated in and contributed to technology communities, advocating for best practices in software engineering and influencing the adoption of new technologies.Optimized SQL queries and performed database schema design for improved application performance.Implemented API service architecture and integrated cloud technologies (AWS) facilitating scalable and flexible application development.Wrote unit and integration tests to ensure application reliability and performance.