Alexander Reinthal's CV

• Phone: +46 70 918 68 50
• Email: [email protected]
• Location: Gothenburg, Sweden
• Website: reinthal.me
• LinkedIn: alexander-reinthal
• GitHub: reinthal

7 years of industry experience - cybersecurity operations - machine learning - data science & engineering

Publications

Detecting Piecewise Cyber Espionage in Model APIs (https://apartresearch.com/project/detecting-piecewise-cyber-espionage-in-model-apis-a8gx)

• Nov 2025
• Arthur Colle, Alexander Reinthal, David Williams-King, Yingquan Li, Lihn Le

Data Modelling for Predicting Exploits (10.1007/978-3-030-03638-6_21)

• Nov 2018
• Reinthal, A, Filippakis, E., Almgren, M.
• Springer LNCS: Nordic Conference on Secure IT Systems

Education

Chalmers Technical University, MS in Engineering Physics

• Sept 2016 – June 2018
• Gothenburg, Sweden
• Coursework: Statistical Physics, Neural Networks and Machine Learning

Gothenburg University, BS in Computer Science

• Sept 2013 – June 2016
• Gothenburg, Sweden
• Coursework: Algorithms, Testing, Debugging and Verification, Theoretical Computer Science, Operating Systems, Cryptography, Cyber Security

Experience

ARENA 7.0, Fellow Participant

• Jan 2026 – Feb 2026
• ARENA prepares fellows for work as researchers in technical AI Safety.
• The curriculum is tought over four high-paced weeks and covers
• the transformer architecture, mechanistic interpretability, RLHF
• evals, working with the Inspect framework and much more.

Knowit Solutions Cocreate, Data Platform Engineer / Tech Lead / Data Scientist

• Feb 2022 – present
• Gothenburg, Sweden
• Mentored junior engineers
• Compared multiple LLM observability tools for use with a job-ad-to-consultant matching LLM platform. (LangChain, Langfuse, Arize Phoenix).
• Deployed Arize Phoenix to monitor LLM calls and model performance in production environments.

NTT Security, Security Analyst

• Apr 2019 – Jan 2022
• Gothenburg, Sweden
• Developed predictive analytics tooling for detecting malicious network traffic, leveraging Python, machine learning, and distributed processing.
• Provided mentorship and security training, educating analysts on threat intelligence, anomaly detection, and alert triage automation.

Ericsson, Python Software Engineer

• June 2017 – Oct 2018
• Gothenburg, Sweden
• Led a team to develop a log parsing and analytics tool that scaled into a dedicated engineering team at Ericsson.

Research Projects

Data Modeling for Predicting Exploits

• 2017 – 2018
• Developed experimental methodology for feature engineering and model validation in cybersecurity domain
• Dsicovered subtle ways that experiments can be compromised, ensuring robust evaluation protocols
• Published peer-reviewed findings in Springer LNCS (DOI: 10.1007/978-3-030-03638-6_21)

Malicious Domain Prediction System

• 2021 – present
• Implemented real-time inference pipeline with performance monitoring

Certificates

• Bluedot AGI Strategy, Completed: 2025-10-07

Technical Projects

Data Breach Analysis Pipeline

• 2024 – present
• Developed scalable data processing pipeline using Apache Iceberg, Flink, and Spark to analyze high-volume breach data
• Passion project to test new technologies that required big data

Open Source Contributions

• Dagster Contribution: PR #24188 – Enhanced workflow orchestration for ML pipeline monitoring
• DLT Hub Contribution: PR #594 – Improved data ingestion reliability for ML applications

Skills

• Machine Learning & AI: PyTorch, XGBoost, SciKit Learn, Jupyter, LLM Observability (LangChain, Langfuse, Arize Phoenix),
• Programming Languages: Python, Javascript, SQL, Rust, C/C++, R, Nix, Terraform
• Research & Data Analysis: Experimental Design, Statistical Analysis, Distributed Processing, Real-time Analytics, Anomaly Detection
• Infrastructure & DevOps: Nix, Docker, Kubernetes, FluxCD, GitOps, CI/CD pipelines, Terraform, AWS (EC2, S3, IAM)
• Data Engineering & Platforms: Spark, Flink, Iceberg, Databricks, Dagster, Snowflake, dbt, Apache Superset