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Kuldeep Jakhar

@kuldeepjakhar

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AI/ML developer focused on deploying scalable machine-learning solutions in the cloud.

India

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What I'm looking for

I’m looking for a role where I can build and deploy AI/ML systems in the cloud, own end-to-end ML workflows, and improve reliability with scalable pipelines and clean APIs—while learning from strong engineering teams.

I’m an AI/ML developer who builds and deploys practical machine-learning workflows—then makes them reliable in real environments. I focus on turning data preprocessing, training, and deployment into end-to-end systems that can run with clear REST API endpoints and monitoring-friendly pipelines.

Recently, as a Cloud/AI Intern at IBM -Edunet Foundation, I developed and deployed a Cloud-based Sentiment Analysis Application. I trained an ML model in Python (Scikit-learn), hosted it on IBM Cloud, and ensured portability through Docker with basic Kubernetes scaling, while working with cloud concepts like IaaS/PaaS/SaaS and deployment models.

Across my internships and projects, I’ve migrated ML workflows to AWS, automated high-confidence data labeling, and built scalable ML pipelines using AWS services and models with LightGBM and TensorFlow. I also enjoy developing full-stack features and responsive interfaces, using tools like React, Flask, and RESTful APIs to ship useful experiences—not just experiments.

Experience

Work history, roles, and key accomplishments

Cloud/AI Intern

IBM - Edunet Foundation

Jul 2025 - Aug 2025 (1 month)

Designed and deployed a cloud-based sentiment analysis app by training an ML model in Python (Scikit-learn) and exposing REST API endpoints for real-time predictions. Containerized deployment with Docker and used basic Kubernetes scaling for portability and deployment reliability.

Cloud Computing Machine Learning Workflows Python scikit learn TensorFlow Docker Kubernetes REST APIs IBM Cloud Sentiment Analysis

Python AI/ML Developer

CSE Pathshala

Jun 2025 - Jul 2025 (1 month)

Migrated ML workflows to AWS to enable automated scalability and improved logging, monitoring, and troubleshooting. Built and deployed scalable ML pipelines using AWS services and implemented models with LightGBM and TensorFlow, including a batch workflow plugin to automate high-confidence data labeling.

AWS Step Functions AWS Batch AWS Lambda S3 DynamoDB Elasticsearch LightGBM TensorFlow Data Labeling

Web Developer Intern

Decent Web Service LLP

Jun 2023 - Jul 2023 (1 month)

Contributed to development and optimization of a School ERP System using HTML5, CSS3, PHP, and MySQL, integrating RESTful APIs and working in Agile (Scrum) workflows. Implemented responsive UI/UX with JavaScript (ES6) to improve cross-browser compatibility, performance, and scalability.