Priyanka Bhutada

AI Researcher

Boston, Massachusetts, United States2 yrs 2 mos experience

Key Highlights

Built a recommendation engine improving user engagement by 22%.
Developed an AI diagnostic tool for lung disease classification.
Automated model training pipelines ensuring consistent performance.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in Data Engineering and Software Development.

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Skills

Core Skills

Machine LearningData AnalysisData EngineeringSoftware Development

Other Skills

Analytical SkillsBERT ModelsBig Data AnalyticsC (Programming Language)C++Collaborative FilteringComputer VisionCore JavaData ModelingData WarehousingDatabase Management System (DBMS)DatabasesDbscanDecision TreesETL Pipelines

About

I’m a Master’s student in Applied Machine Intelligence at Northeastern University with 2.5 years of industry experience building end-to-end machine learning solutions across NLP, computer vision, and explainable AI. My work focuses on developing reliable, interpretable models that solve real-world problems, not just optimize metrics. At Accenture and Whiteklay Technologies, I led projects that included building a recommendation engine that processed over 2 million user logs, real-time anomaly detection pipelines for cloud systems, and a predictive analytics system that reduced reporting time by 40%. More recently, I developed an AI diagnostic tool for lung disease classification (ILD, Pneumonia, COVID-19, Normal) using CNNs and Grad-CAM to support early diagnosis. I’m actively seeking internships or full-time opportunities where I can contribute to building scalable, trustworthy ML systems. I bring a strong foundation in Python, SQL, TensorFlow, and MLOps tools combined with a passion for turning data into decisions that matter.

Experience

Northeastern university

Instructional Assistant

Aug 2025 – Present · 7 mos

Whiteklay

SDE-2

Apr 2024 – Aug 2024 · 4 mos · Pune, Maharashtra, India · On-site

My roles and responsibilities:
1. Built a recommendation system using collaborative filtering and implicit feedback techniques, improving personalization accuracy by 25% for a client in the media domain
2. Implemented sentiment analysis using pre-trained BERT models to classify customer feedback, helping reduce churn by segmenting users based on satisfaction levels
3. Automated model training and validation pipelines using Scikit-learn and MLflow, ensuring consistent performance across hyperparameter tuning experiments

Collaborative FilteringImplicit Feedback TechniquesSentiment AnalysisBERT ModelsScikit-learnMLflow+2

Accenture

2 roles

Software Engineering Analyst

Promoted

Jun 2022 – Nov 2022 · 5 mos

My roles and responsibilitie:
1. Designed and deployed Python + SQL-based ETL pipelines handling 10M+ records weekly, reducing reporting latency by 35%
2. Built a collaborative filtering-based recommendation engine that improved user engagement by 22% using Spark and pandas
3. Automated anomaly detection in server logs using XGBoost and SHAP, enabling real-time alerts with 90% precision
4. Recognized for contributions with a promotion.

PythonSQLETL PipelinesSparkpandasXGBoost+3