Available to hire
Hi! I’m Taimoor Khan, an AI Engineer with extensive experience designing and deploying cutting-edge machine learning models across healthcare, retail, energy, and industrial sectors. I thrive on leveraging AI technologies like LSTM, transformers, GANs, and federated learning to solve real-world problems and deliver impactful data-driven solutions.
I’m passionate about collaboration and leadership, having led teams on projects ranging from real-time edge AI applications to NLP-driven resume screening tools. I’m always eager to explore new AI techniques and translate complex data into actionable insights that empower businesses and improve lives.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Language
English
Fluent
Work Experience
AI Engineer at Ninth Dev Solutions
December 31, 2024 - July 21, 2025Engineered and deployed a predictive analytics platform leveraging LSTM networks to process EHR data from 15 hospitals, accurately forecasting patient health trajectories and potential adverse events. Implemented unsupervised learning techniques (K-Means, PCA) on hospital operational data, identifying efficiency bottlenecks and resource utilization patterns, resulting in a 12% reduction in operational costs and 18% improvement in resource allocation efficiency. Collaborated on a robust ensemble model (stacking XGBoost and LSTM) for high-accuracy solar energy output forecasting using multivariate time-series environmental data. Designed, trained, and deployed GRU-based sequence models to process over 5TB of retail transaction data, uncovering predictive consumer behavior patterns such as purchase propensity and churn risk. Created dynamic Tableau dashboards connected to the retail data lake, enhancing data accessibility for non-technical stakeholders by 40% and enabling data-driven inve
AI Engineer at Ninth Dev Solutions
December 31, 2024 - July 21, 2025Engineered and deployed a predictive analytics platform leveraging LSTM networks to process EHR data from 15 hospitals, accurately forecasting patient health trajectories and potential adverse events. Implemented unsupervised learning techniques (K-Means, PCA) on hospital operational data, identifying efficiency bottlenecks and resource utilization patterns, resulting in a 12% reduction in operational costs and 18% improvement in resource allocation efficiency. Collaborated on a robust ensemble model (stacking XGBoost and LSTM) for high-accuracy solar energy output forecasting using multivariate time-series environmental data. Designed, trained, and deployed GRU-based sequence models to process over 5TB of retail transaction data, uncovering predictive consumer behavior patterns such as purchase propensity and churn risk. Created dynamic Tableau dashboards connected to the retail data lake, enhancing data accessibility for non-technical stakeholders by 40% and enabling data-driven inve
AI Engineer at Medical Diagnosis Support System
April 30, 2024 - July 21, 2025Co-developed a transformer-based model (adapting ViT and BERT principles) within a 3-person agile team, integrating medical imaging, clinical notes, and vital signs for robust, explainable diagnostic support. Implemented multi-head attention mechanisms and optimized loss functions (e.g., focal loss) to handle class imbalance, achieving a 92% F1-score and a 28% reduction in clinically relevant false negatives.
AI Engineer at Privacy-Preserving Learning Framework
December 31, 2023 - July 21, 2025Architected and built a federated learning system with secure aggregation protocols (SMPC) for collaborative model training on distributed, sensitive datasets without centralizing raw data. Integrated advanced privacy-enhancing techniques, notably ε-differential privacy, maintaining 90% of centralized model performance while ensuring compliance with regulations like HIPAA.
AI Engineer at Intelligent Control Systems
September 30, 2023 - July 21, 2025Designed and implemented advanced RL algorithms (PPO, DDPG) for industrial control and optimization problems in collaboration with a university research team. Engineered novel reward mechanisms and used domain randomization in OpenAI Gym simulations, accelerating training convergence by 45% and improving robustness to environmental variations.
AI Engineer at Synthetic Data Generation Platform
June 30, 2023 - July 21, 2025Developed and refined an advanced GAN framework (StyleGAN-based) for generating high-fidelity synthetic data in data-scarce domains like medical imaging and financial fraud detection. Implemented spectral normalization and progressive growing, achieving an 82% quality improvement (FID score) and enabling downstream AI model development in previously limited scenarios.
AI Engineer at Ninth Dev Solutions
December 31, 2024 - July 22, 2025Engineered and deployed a predictive analytics platform leveraging LSTM networks to process EHR data from 15 hospitals, accurately forecasting patient health trajectories and potential adverse events. Implemented unsupervised learning techniques (K-Means, PCA) on hospital operational data, identifying efficiency bottlenecks and resource utilization patterns, resulting in a 12% reduction in operational costs and 18% improvement in resource allocation efficiency. Collaborated on a robust ensemble model (stacking XGBoost and LSTM) for high-accuracy solar energy output forecasting using multivariate time-series environmental data. Designed, trained, and deployed GRU-based sequence models to process over 5TB of retail transaction data, uncovering predictive consumer behavior patterns such as purchase propensity and churn risk. Created dynamic Tableau dashboards connected to the retail data lake, enhancing data accessibility for non-technical stakeholders by 40% and enabling data-driven inve
Education
bachelor in artificial intelligence at Pak-Austria Fachhochschule Institute of Applied Sciences and Technology
October 17, 2022 - June 21, 2026Qualifications
Industry Experience
Healthcare, Retail, Energy & Utilities, Software & Internet, Financial Services, Professional Services
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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