i
ikramdkhan

Ikram

@ikramdkhan
5.0(40)

Machine Learning Engineer, AI Chatbots, ML Models and Data Science

Pakistán
Inglés
Parte de la información aparece en idioma inglés.
Sobre mí
I am a Machine Learning Engineer with M.Sc. in Data Science from RWTH Aachen University, Germany. I build AI chatbots, custom ML models, data analysis pipelines, and business automation systems that deliver results. My work includes clinical AI systems (AUC 0.978), RAG-powered chatbots, and production NLP pipelines built in professional research and enterprise environments. I work with Python, PyTorch, scikit-learn, OpenAI, Claude, and LangChain. 10+ years in tech. I do not use templates or no-code shortcuts; I engineer real solutions. Message me before ordering and let us discuss your project... Lee más

Habilidades

i
ikramdkhan
Ikram
desconectado • 

Revisa mis servicios

Sitio web UI/Diseño UX
I will do adobe xd, figma ui ux design mockup for website, app and dashboard
5.0(16)
WordPress
I will develop, fix custom wordpress website for companies by avad, divi, gravity forms
5.0(9)

Porfolio

Experiencia laboral

Research Assistant

Uniklinik RWTH Aachen • Tiempo parcial

Aug 2024 - Dec 20251 yr 4 mos

Built end-to-end ML systems for clinical decision support in the ICU, working with MIMIC-III/IV critical care data under PhysioNet data-use protocols. - Designed and trained an LSTM-based ICU mortality predictor achieving AUC 0.978 and AP 0.892, with strict patient-level splits, temporal windowing (6–12 h bins), leakage controls, and model calibration. - Built a production RAG pipeline for clinical notes: Bio_ClinicalBERT embeddings, FAISS indexing, DSPy-structured prompt chains, local LLaMA generation; served via FastAPI with an evaluation harness (precision@k, answer faithfulness). - Delivered clinician-facing explainability dashboards using XGBoost and SHAP, improving trust in high-risk mortality flags and reducing black-box concerns. - Implemented model monitoring (prediction drift, feature distribution checks) and automated retraining triggers; containerized all services with Docker and deployed on Azure with CI/CD. - Used DSPy-driven prompt optimization to generate augmented clinical notes grounded in historical data, expanding rare-case coverage in offline evaluations. Stack: Python, PyTorch, scikit-learn, XGBoost, SHAP, LangChain, DSPy, Bio_ClinicalBERT, LLaMA, FAISS, FastAPI, Docker, Azure

Working Student Artificial Intelligence / Machine Learning

aixigo AG • Tiempo parcial

Jan 2023 - Apr 20241 yr 3 mos

Shipped LLM-powered features and ML microservices for Aixigo’s Bloxx wealth management platform, working across the full stack from data pipelines to production deployment. - Built the Smart Portfolio Insider : LLM-powered analytics over financial dataframes with RAG, prompt guardrails, streaming I/O, and robustness checks for client use. - Productionized ML microservices (PyTorch, scikit-learn) via Flask/FastAPI and Docker with GitLab/Jenkins CI pipelines; significantly reduced manual deployment overhead. - Authored shell/Python ETL pipelines for large-scale portfolio data processing; improved data freshness for downstream model training and analytics workloads. - Owned automated testing (FitNesse), developer documentation (MkDocs), and Agile delivery (Jira sprints); contributed Java API services for platform integration. Stack: Python, PyTorch, scikit-learn, LangChain, DSPy, Flask, FastAPI, Docker, Jenkins, GitLab CI, Java, SQL

Technical Consultant

Buzzware Tech • Tiempo completo

Sep 2019 - Oct 20201 yr 1 mo

Led end-to-end product delivery for multiple client projects, bridging technical execution with business requirements. - Introduced Agile/Kanban workflows across the team, improving delivery cadence and stakeholder visibility. - Designed data warehouse schemas and ETL pipelines feeding Power BI dashboards for client reporting and decision-making. Stack: Python, SQL, Power BI, ETL, Agile/Kanban

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