Kapil Gaur

• Designed and deployed end-to-end machine learning pipelines for regression, classification, clustering, and time-series forecasting using scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM. • Developed LLM applications using OpenAI, Azure OpenAI, LLaMA, LangChain, and agentic AI workflows using Langgraph reducing manual effort by 40–60%. • Built and deployed FastAPI/Flask microservices powering ML & LLM models, reducing response latency by 35%.

• Led development of AI/ML, NLP, RAG, and Generative AI solutions using Python, Transformers, LLMs, resulting in 30–45% improvement in automation and model accuracy across use cases. • Designed and deployed ML pipelines, feature engineering workflows, and automated data processes using Docker, MLflow, and CI/CD platforms. • Built NesGPT, a KNIME-based AI assistant using OpenAI and LLaMA models, improving internal analytics productivity and stakeholder decision-making.

• Built predictive models to identify failure risks for cloud-based hardware systems through log analysis, improving early-warning detection accuracy. • Developed Python-based regression and classification simulation models to test failure scenarios and recommend device maintenance strategies. • Built predictive maintenance models using ML and NLP to analyse device logs and identify early hardware failure risks. • Improved failure prediction accuracy by optimizing hyperparameters and implementing workflows.

• Automated SOC documentation using NLP and ML, reducing manual effort by 70%. • Built ML workflows in Python reducing processing time and improving model performance. • Supported operational analytics by generating insights used for capacity planning and device health monitoring. • Built dashboards (Power BI/Tableau) to translate analytics outputs into executive-level recommendations.

• Developed ML/NLP models to automate BoQ and SoC sheet automation in an RFP, reducing manual efforts by 40%. • Performed population-level device health analysis using Python and statistical models. • Partnered with cross-functional engineering teams to define model logic and reporting structures.

• Supported network operations and coordinated with UK teams to expedite issue resolution.

• Performed hardware testing for telecom equipment and ensured compliance with QA standards.