Available to hire
Hi, I’m Radhika Tekade, an AI/ML Engineer based in Kennewick, WA. I specialize in building scalable ML solutions across machine learning, deep learning, NLP, and computer vision, with hands-on work in Python, TensorFlow, PyTorch, Scikit-Learn, and cloud platforms like AWS and Azure. I’ve shipped production-grade ML pipelines and DL applications, and I love turning data into actionable business insights.
I’m passionate about ethics, explainability, and model optimization, driving data-driven decision making and business transformation. I enjoy collaborating with cross-functional teams to deploy robust AI systems that are reliable, transparent, and scalable.
Skills
Language
English
Fluent
Work Experience
AI / Machine Learning Engineer at CVS Health
February 1, 2024 - PresentFinetuned transformer models (BioBERT, GPT-3, ClinicalBERT) on 10M+ unstructured data, achieving F1 score of 0.92 in collaboration with clinical teams. Delivered deep learning imaging solutions (U-Net, Mask R-CNN) on 100K+ scans, achieving Dice score of 0.9 and reducing annotation time by 40%. Built retrieval-augmented generation pipelines (RAG) with FAISS, Hugging Face, and GenAI handling 1M+ queries, improving contextual search accuracy by 25%. Performed feature engineering and preprocessing (normalization, encoding, PCA, clustering) to improve baseline models by ~12% and enhance interpretability. Designed CI/CD-enabled ML pipelines with monitoring and automated retraining on AWS SageMaker, Lambda, and GCP, achieving 99% uptime and scalable cross-team deployments. Applied reinforcement learning and personalization techniques to recommendation-like tasks, driving data-driven decision making and business transformation.
ML Engineer
August 1, 2021 - October 15, 2025Engineered anomaly detection models (XGBoost, Scikit-Learn) analyzing 1M+ financial transactions, boosting fraud detection accuracy by 18% and reducing false positives by 22%. Automated document classification with NLP (SpaCy, Transformers), processing 80% of financial forms automatically and cutting compliance review time by 40%. Built real-time ML pipelines on Spark + Databricks for streaming analytics and anomaly detection with ~95% accuracy. Developed computer vision–based identity verification systems (OpenCV, CNNs), reducing manual KY/CY effort by 60% and enhancing security. Conducted feature selection, model validation, and hyperparameter tuning to ensure reliability and regulatory compliance. Created Power BI dashboards to visualize financial trends and model performance, improving reporting efficiency by 30%.
Education
M Eng in Robotics, Mechatronics, & Automation at Oregon State University
January 1, 2021 - January 1, 2023B Tech in Mechanical Engineering at VNIT, India
January 1, 2016 - January 1, 2020Qualifications
Industry Experience
Healthcare, Software & Internet
Skills
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