Charan Sai

AI & ML Engineer @ JCPenney

About

Innovative and impact-driven AI & ML Engineer with 4+ years of experience in designing, deploying, and optimizing machine learning solutions in cloud-native environments. Expertise in deep learning, NLP, MLOps, and scalable model deployment, including fine-tuning large language models (Gemini, PaLM, BERT) and developing privacy-preserving, production-grade AI systems. Proficient in Python, TensorFlow, PyTorch, Google Cloud (Vertex AI, TPUs), and machine learning tools such as Scikit-learn, Keras, and Apache Airflow. Demonstrated success in improving model performance, reducing training times, and optimizing query accuracy. Experienced in developing end-to-end ML pipelines, automating model monitoring, A/B testing, and CI/CD, improving deployment frequency. Strong background in anomaly detection, network traffic forecasting, and NLP-based automation. Skilled in model evaluation, hyperparameter tuning, and improving AI explainability with tools like SHAP, LIME, and ELI5. Adept at translating AI research into scalable, impactful solutions and collaborating across teams to drive innovation.

Country

United States

City

Pleasant Prairie

Industry

Computer Software

Skill

Deep Learning, MLOps, PyTorch, AWS SageMaker, CI/CD pipelines , Natural Language Processing (NLP), ARIMA, Long Short-term Memory (LSTM), Docker, Kubernetes, TensorFlow, Vertex AI , SQL, Google BigQuery, ViTs, Data Pipelines, Machine Tools, Solution Architecture, Microsoft Office, Apache Spark, Apache hive

Experience

AI & ML Engineer

JCPenney

2024-4 - Present · 2 yrs 6 mos

Texas, United States

• Spearheaded AI-driven retail transformation initiatives at JCPenney, focusing on customer personalization and demand forecasting. • Leveraged cloud ML tools such as Vertex AI and BigQuery to enhance pricing optimization and supply chain analytics. • Drove data-driven decision-making processes that improved sales forecasting accuracy and increased recommendation engagement.

AI & ML Engineer

Mallika Engineers Consultancy Services

2019-9 - 2022-11 · 3 yrs 3 mos

India

• Designed and implemented scalable ML models for network analytics, enhancing anomaly detection accuracy by 30% and reducing false positives by 25% using Python, TensorFlow, and PyTorch. • Developed NLP-based chatbots and automation scripts to streamline IT operations, resulting in 40% reduction in manual intervention and improved customer support efficiency. • Enhanced network traffic forecasting using time-series models (e.g., LSTM, ARIMA), achieving 95% prediction accuracy and enabling proactive resource allocation. • Built CI/CD pipelines for ML models using Docker, Kubernetes, and AWS SageMaker, cutting deployment time by 50% and ensuring smooth model rollouts. • Applied hyperparameter tuning techniques (grid/random search, Bayesian optimization) and cross-validation, boosting precision-recall by 15–20%. Ensured AI explainability with tools like SHAP, LIME, and ELI5. • Developed LLM-based automation solutions using LangChain and Hugging Face, reducing manual documentation effort by 50%. Fine-tuned models with Reinforcement Learning with Human Feedback (RLHF), improving accuracy by 35%. • Excelled in cross-functional collaboration, effectively communicating AI/ML strategies to technical and non-technical stakeholders while ensuring high standards in model development, testing, and documentation.