Ninad Dixit
Ai Resident @Apziva
Signup · Get unlimited contacts
WORK HISTORY
Ai Resident @Apziva
Toronto, ON, CA
Delivered a computer vision solution for page-flip detection, achieving 97% F1-score and 96% sequence-level accuracy, enabling fast and high-quality document scanning in bulk.• Built an NLP-driven candidate ranking system that automatically identifies top talent, reducing manual screening time by 90% across a pool of 100+ candidates.• Designed and deployed a scalable embedding pipeline to power semantic search over candidate profiles, eliminating manual feature engineering and enabling real-time retrieval.• Developed a machine learning model to predict customer satisfaction in logistics and delivery, achieving 73%+ accuracy and generating insights to improve service quality.
EDUCATION
Institute Of Chemical Technology
Bachelor of Technology (B.Tech.)
Virginia Tech
Master of Science - MS
Virginia Tech
Doctor of Philosophy - PhD
SKILLS
ABOUT NINAD DIXIT
Build production-grade AI/ML systems that turn complex scientific data into actionable business impact across healthcare, biotech, and fintech. Combine a PhD in Chemistry with 10+ years of R&D and hands-on machine learning engineering to bridge the gap between research and scalable deployment.Deliver end-to-end machine learning solutions - from problem framing and data strategy to model development, validation, and deployment - using Python (scikit-learn, TensorFlow, PyTorch) and cloud platforms (AWS), with a strong focus on MLOps, reproducibility, and performance at scale.Translate cutting-edge methods including deep learning, NLP, and quantum-inspired optimization (Qiskit, QUBO, VQE) into real-world applications such as drug response prediction, process optimization, and risk modeling.Partner cross-functionally with product, engineering, and leadership teams to align technical solutions with business outcomes, accelerate decision-making, and deliver measurable value.Bring a builder mindset shaped by startup experience—moving quickly from idea to prototype to production while maintaining strong analytical rigor and stakeholder alignment.Focused on opportunities as a Data Scientist or Machine Learning Engineer in Toronto, particularly within healthcare AI, life sciences, and fintech teams solving high-impact problems.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.