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I am a ML engineer with hands-on experience in building scalable recommendation systems and anomaly detection pipelines that boost personalization accuracy and reliability. I thrive in cross-functional teams, turning complex data into actionable insights and robust ML solutions. I specialize in end-to-end ML workflows, from data engineering to model deployment, using Python, TensorFlow, PyTorch, and AWS to deliver impactful results and continuous improvements.…I am a ML engineer with hands-on experience in building scalable recommendation systems and anomaly detection pipelines that boost personalization accuracy and reliability. I thrive in cross-functional teams, turning complex data into actionable insights and robust ML solutions. I specialize in end-to-end ML workflows, from data engineering to model deployment, using Python, TensorFlow, PyTorch, and AWS to deliver impactful results and continuous improvements.

Riya Gupta

Data Scientist, AI Engineer, Full Stack Developer, +1

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I am a ML engineer with hands-on experience in building scalable recommendation systems and anomaly detection pipelines that boost personalization accuracy and reliability. I thrive in cross-functional teams, turning complex data into actionable insights and robust ML solutions. I specialize in end-to-end ML workflows, from data engineering to model deployment, using Python, TensorFlow, PyTorch, and AWS to deliver impactful results and continuous improvements.…I am a ML engineer with hands-on experience in building scalable recommendation systems and anomaly detection pipelines that boost personalization accuracy and reliability. I thrive in cross-functional teams, turning complex data into actionable insights and robust ML solutions. I specialize in end-to-end ML workflows, from data engineering to model deployment, using Python, TensorFlow, PyTorch, and AWS to deliver impactful results and continuous improvements.

Available to hire

I am a ML engineer with hands-on experience in building scalable recommendation systems and anomaly detection pipelines that boost personalization accuracy and reliability. I thrive in cross-functional teams, turning complex data into actionable insights and robust ML solutions.

I specialize in end-to-end ML workflows, from data engineering to model deployment, using Python, TensorFlow, PyTorch, and AWS to deliver impactful results and continuous improvements.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Work Experience

Artificial Intelligence Intern at Avkalan.ai

September 1, 2023 - May 1, 2024

Engineered a hybrid recommendation system combining TF-IDF content filtering and ALS-based collaborative filtering models using PyTorch; improved personalization accuracy by 25% across a dataset of 1M+ user-item interactions. Developed and deployed anomaly detection pipelines (isolation forest and autoencoder) using TensorFlow, flagging irregular patterns and reducing undetected anomalies by 30%. Optimized large-scale data preprocessing workflows (1M+ records) with Python, Pandas, and scikit-learn, accelerating model training by 40%. Leveraged AWS (SageMaker, EC2, Lambda) for distributed training and deployment, enabling scalable inference and near real-time feature updates.

Junior Data Engineer at Garvis

November 1, 2022 - January 31, 2023

Built scalable data pipelines in Python, DBT, and AWS Glue to prepare tabular datasets for ML model training, improving data processing efficiency by 45% and reducing feature extraction latency. Developed automated validation and monitoring workflows with Great Expectations to ensure high-quality, unbiased training data, boosting model reliability and analytics accuracy by 25%. Partnered with AI teams to integrate pipelines with SageMaker and Redshift, enabling real-time feature updates and supporting continuous model retraining for production ML applications.