10.09.2026 aktualisiert
40 % teilweise verfügbar
Machine Learning Engineering Lead | AI Governance | ISO 42001 | Healthcare & Biotech
Zurich, Schweiz
Nur Remote
MSc. Computational Biology & Bioinformatics, Deep Learning - ETH Zurich (2021-2023)Über mich
Machine Learning engineering Lead with 5+ years of experience deploying deep learning systems in healthcare and biotech. Track record in research (NeurIPS), patents, and real-world ML pipelines. Expertise spans AIMS (ISO/IEC 42001), AI Risk Management, RL, Graph Neural Networks, and Generative AI.
Skills
QualitätsauditISO13485Machine LearningRisikoanalysePyTorchDeep Learning
Machine Learning & Deep Learning
Expertise in Reinforcement Learning, Graph Neural Networks, Generative Models, and Wearable ML with 5+ years of experience deploying deep learning systems in healthcare and biotech environments.
AI Governance & Risk Management
Implementation of Artificial Intelligence Management Systems aligned with ISO/IEC 42001, including AI Risk Assessments, AI Impact Assessments, model governance processes, data lineage, monitoring, and V&V procedures.
MLOps & Cloud Pipelines
Design and operation of ISO-compliant CI/CD workflows, large-scale cloud pipelines on GCP and Azure, Docker, TFX, and AIMS implementation for production ML systems.
Graph Neural Networks (GNNs)
Application of GNNs combined with contrastive learning for pharmacokinetic modeling, achieving +15% over SOTA, and use of 3D GCN for docking pose evaluation outperforming SOTA by 20%.
Protein Design & Bioinformatics
Development of a novel generative protein design architecture with hierarchical equivariant modeling, published at NeurIPS Conference, and creation of ProteinFlow, an open-source protein structure library.
Programming
Proficiency in Python, PyTorch, TensorFlow, and C++ for building and deploying machine learning models and data pipelines.
Data Pipeline Engineering
Design of data pipelines aggregating 5M+ records from 10+ heterogeneous sources, supporting large-scale research projects such as Type 1 Diabetes research.
Computer Vision
Development of computer vision models for autonomous maritime drones, achieving 80%+ accuracy in ship detection.
Responsible AI & AI Policy
Development of AI policies, documentation of AIMS processes, and collaboration with engineering and management teams to operationalize responsible AI practices.
Expertise in Reinforcement Learning, Graph Neural Networks, Generative Models, and Wearable ML with 5+ years of experience deploying deep learning systems in healthcare and biotech environments.
AI Governance & Risk Management
Implementation of Artificial Intelligence Management Systems aligned with ISO/IEC 42001, including AI Risk Assessments, AI Impact Assessments, model governance processes, data lineage, monitoring, and V&V procedures.
MLOps & Cloud Pipelines
Design and operation of ISO-compliant CI/CD workflows, large-scale cloud pipelines on GCP and Azure, Docker, TFX, and AIMS implementation for production ML systems.
Graph Neural Networks (GNNs)
Application of GNNs combined with contrastive learning for pharmacokinetic modeling, achieving +15% over SOTA, and use of 3D GCN for docking pose evaluation outperforming SOTA by 20%.
Protein Design & Bioinformatics
Development of a novel generative protein design architecture with hierarchical equivariant modeling, published at NeurIPS Conference, and creation of ProteinFlow, an open-source protein structure library.
Programming
Proficiency in Python, PyTorch, TensorFlow, and C++ for building and deploying machine learning models and data pipelines.
Data Pipeline Engineering
Design of data pipelines aggregating 5M+ records from 10+ heterogeneous sources, supporting large-scale research projects such as Type 1 Diabetes research.
Computer Vision
Development of computer vision models for autonomous maritime drones, achieving 80%+ accuracy in ship detection.
Responsible AI & AI Policy
Development of AI policies, documentation of AIMS processes, and collaboration with engineering and management teams to operationalize responsible AI practices.
Erfahrung
Berufserfahrung5 - 10 Jahre
Freelancer seit2024
Sprachen
ArabischMutterspracheDeutschGrundkenntnisseEnglischverhandlungssicherFranzösischverhandlungssicher
Projekthistorie
Led the implementation of the Artificial Intelligence Management System (AIMS) aligned with ISO/IEC 42001. Conducted AI Risk Assessments and AI Impact Assessments, established model governance processes, and mapped ISO/IEC 42001 controls into CI/CD workflows. Developed AI policies and documented AIMS processes. Designed a data pipeline aggregating 5M+ records from 10+ heterogeneous sources for Type 1 Diabetes research. Developed and patented an RL controller outperforming SOTA by 18% using differential programming and hybrid ML models.
Published at a NeurIPS Conference a novel generative protein design architecture with hierarchical equivariant modeling. Built ProteinFlow, an open-source protein structure library adopted by biotech researchers.
Applied GNNs and contrastive learning to pharmacokinetic modeling, achieving +15% over SOTA. Co-authored a peer-reviewed publication in Journal of Chemical Information and Modeling.