Open to opportunities

Thomas Hoffmann

@thomashoffmann

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Senior AI engineer specializing in NLP, agentic systems, and AI infrastructure.

Switzerland

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What I'm looking for

I seek roles building production NLP and agentic AI systems with strong engineering teams, focusing on scalable infrastructure, responsible AI, and impactful healthcare or research applications.

I am a Senior AI Engineer focused on NLP, agentic workflows, and responsible AI, with 7+ years building production ML systems across MedTech, quantum AI research, and infrastructure startups.

I lead small engineering teams to design scalable multi-agent assistants, knowledge-graph driven systems, PHI-redaction and clinical extraction pipelines, and auto-scalable AI pipelines that drastically reduced manual review and annotation time.

My background includes applied quantum NLP research, publishing peer-reviewed papers, and shipping toolboxes and training modules across multiple backends; I combine strong Python engineering (8+ years) with practical MLOps, human-in-the-loop design, and a commitment to trustworthy AI.

Experience

Work history, roles, and key accomplishments

Current

Senior AI Engineer

Current

ARTIDIS

Feb 2024 - Present (1 year 11 months)

Leading a team of 3 AI engineers to develop agentic AI systems for medical data analysis, integrating a multi-agent assistant and knowledge-graph workflows that cut human review time for PHI and clinical extraction by 85%.

NLP Knowledge Graphs Python PHI Redaction Data Visualization Team Leadership

Research Engineer

Quantinuum

Nov 2021 - Jan 2024 (2 years 2 months)

Maintained and extended lambeq to support scalable training across PyTorch, JAX, TensorFlow and NumPy, and developed a novel gradient estimation technique improving QML parameter-scaling from O(n) to O(1); published peer-reviewed work on QML and XAI.

Python PyTorch Jax TensorFlow Lambeq Gradient Estimation Explainable AI

Machine Learning Engineer

Vialytics

Apr 2018 - Sep 2019 (1 year 5 months)

First full-time hire who developed ML pipelines and human-in-the-loop labeling systems for municipal infrastructure monitoring, achieving 80%+ object-detection accuracy and reducing annotation time by 90% while building auto-scalable GCP pipelines to lower infra costs.

Computer Vision Object Detection GCP MLOps Human In The Loop Python

Education

Degrees, certifications, and relevant coursework

Chalmers University of Technology

Master of Science, Complex Adaptive Systems

2019 - 2021

Grade: 3.8/4.0

Completed a Master of Science in Complex Adaptive Systems with a 3.8/4.0 GPA, focusing on interdisciplinary adaptive systems and applied machine learning methods.