Implementing end-to-end LLMOps solutions to manage, deploy, monitor, and optimize large language models in production environments, ensuring high availability, scalability, and performance.

Engineered an innovative image detection model tailored for a major US telecommunications client.

Implementing the model to detect and manage inventories of mobile towers, leading to a substantial revenue increase of $.2-.5M annually.

Built ML algorithms that power millions of users to discover relevant content generating billions of page views.

Created Deep Learning algorithms using NLP techniques to sift through thousands of news articles being published every minute and bring the most relevant content to each individual user.

Spearheaded the development of advanced models for an EdTech company, implementing AI color contrast and PDF AI auto-zoning using Image Detection methodologies.

Developed predictive models using Deep Learning and NLP techniques.

Built Artificial Neural Network using TensorFlow in Python to identify the customer’s probability of canceling the connection (Churn Model).

Applied ML algorithms and statistical modeling like decision trees, text analytics, NLP, supervised and unsupervised algorithm, regression models, classification models, social network analysis, neural-net, Deep Learning, and clustering using scikit-learn.

Worked with 8+ country operators, providing ML/DL-based solutions, improving network by 5-40%, and increasing customers by 10-35%.

Worked independently and guided teams on Sentiment Analysis, capacity prediction, throughput prediction, CAPS time series forecasting, etc.

Performed daily analytics activity by monitoring daily KPIs using Citrix and BO for 3 countries.

Worked as an UMTS engineer on a 3G project for Vodafone (rollout and optimization) for Delhi circle.

Did EDA and RCA to get insights from data and worked on KPI optimization and parameter tuning based on statistical models.