Khushal Khare

Master Thesis Student at Dilax Intercom, Berlin

Designed scalable ML pipelines on GCP and Azure using Apache Airflow to orchestrate data ingestion, preprocessing, training, and deployment. Built reusable Python components with PySpark and Pandas for distributed preprocessing and feature engineering on large-scale datasets. Developed CI/CD workflows using GitLab CI, enabling automated testing, version-controlled deployment, and rollback capabilities. Containerized and deployed real-time inference services with Docker on Kubernetes clusters, supporting scalable production analytics. Applied MLOps practices, including model drift detection, automated validation, continuous training, and pipeline observability. Built monitoring dashboards using Prometheus and Grafana to track pipeline health, resource usage, and alerting for proactive maintenance.

Work Student at Dilax Intercom, Berlin

Built production-grade ETL pipelines with Python, Apache Airflow, and BigQuery for near real-time processing of API and data lake sources. Developed cloud-native ML pipelines using TensorFlow, Scikit-learn, and Vertex AI, covering training, tuning, deployment, and monitoring. Automated data ingestion workflows to support dynamic datasets and continuous model updates. Collaborated with DevOps teams to containerize services and deploy via Helm on Kubernetes, ensuring high availability and scalability. Enhanced CI/CD pipelines with secure deployment practices, test automation, and multi-environment management. Created interactive dashboards using Plotly Dash; integrated processed data and models into PostgreSQL and BigQuery for analytics and product insights.

Associate Engineer - Android/Java at Foxconn Technology Group, India

Developed Android applications using Java and Kotlin, adhering to MVVM and MVP architectures for clean, modular, and testable codebases. Built and maintained RESTful APIs to facilitate seamless client-server communication. Implemented multithreaded processing using Executors, LiveData, and WorkManager for efficient background operations. Integrated Dagger-Hilt for dependency injection and Room for local data persistence and offline-first experiences. Applied core design patterns to build maintainable, reusable components. Wrote and maintained unit and UI tests with JUnit, Mockito, and Espresso to ensure stability and code quality. Used Git, JIRA, and Jenkins for version control, CI/CD, and Agile project management in cross-functional teams.

Machine Learning Intern at Grroom, India

Worked on YOLO-based image processing pipeline, converting images into numerical representations for model input and evaluation. Designed and executed model performance testing workflows, achieving improved accuracy and inference speed in 3 out of 4 YOLO variants over 3 months. Applied data preprocessing, model benchmarking, and performance metrics analysis to support iterative model tuning.

Associate Engineer - Android / Java at Foxconn Technology Group, India

Developed Android applications using Java and Kotlin, adhering to MVVM/MVP architectures; Built and maintained RESTful APIs for client–server communication; Implemented multi-threaded processing with Executors, LiveData, and WorkManager; Integrated Dagger-Hilt for dependency injection and Room for local persistence and offline-first experiences; Wrote unit and UI tests with JUnit and Espresso; Collaborated with cross-functional teams; Used Git, Jira, and Jenkins for version control, CI/CD and agile project management.

Machine Learning Engineer at Dila Intercom, Berlin

Built production-grade ETL pipelines with Python, Apache Airflow, and BigQuery for near real-time processing of API and data lake sources. Developed cloud-native ML pipelines using TensorFlow, Scikit-Learn, and Vertex AI, covering training, tuning, deployment, and monitoring. Automated data ingestion workflows for dynamic datasets and continuous model updates. Collaborated with DevOps teams to containerize services and deploy via Helm on Kubernetes, ensuring high availability and scalability. Enhanced CI/CD with secure deployment practices and multi-environment management. Created interactive dashboards using Plotly Dash and integrated processed data and models into PostgreSQL and BigQuery for analytics and product insights.

ML/ETL Engineer Intern at DilaX Intercom, Berlin

Built production-grade ETL pipelines with Python, Apache Airflow, and BigQuery for near real-time processing of API and data lake sources. Developed cloud-native ML pipelines using TensorFlow, Scikit-learn, and Vertex AI, covering training, tuning, deployment, and monitoring. Automated data ingestion workflows to support dynamic datasets and continuous model updates. Collaborated with DevOps teams to containerize services and deploy via Helm on Kubernetes clusters.

Android Developer at Android/Java-Focused Technology Group, India

Developed Android applications using Java and Kotlin following MVVM and MVP architectures for a clean, modular, and testable codebase. Built and maintained RESTful APIs to support client-server communication. Implemented multi-threaded processing using Executor, LiveData, and WorkManager for efficient background operations. Integrated Dagger-Hilt for dependency injection and Room for local data persistence and offline-first experiences. Applied core design patterns to build maintainable, reusable components. Wrote and maintained unit and UI tests with JUnit, Mockito, and Espresso to ensure stability and code quality. Used Git, JIRA, and Jenkins for version control, CI/CD, and Agile project management in cross-functional teams.

Machine Learning Intern at Room, India

Worked on YOLO-based image processing pipeline, converting images into numerical representations for model input and evaluation.