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Hi, I’m Felix Falkenberg — a DevOps & ML Engineer focused on bringing machine learning from prototype to production. I design and operate scalable, cloud-native ML platforms and microservices, with deep hands-on experience in Kubernetes, Docker, and AWS. With a background in psychology and a minor in computer science, I enjoy solving real-world problems in healthcare by translating research questions into robust models and data workflows. I thrive in cross-functional teams and love turning complex concepts into actionable, data-driven results.…Hi, I’m Felix Falkenberg — a DevOps & ML Engineer focused on bringing machine learning from prototype to production. I design and operate scalable, cloud-native ML platforms and microservices, with deep hands-on experience in Kubernetes, Docker, and AWS. With a background in psychology and a minor in computer science, I enjoy solving real-world problems in healthcare by translating research questions into robust models and data workflows. I thrive in cross-functional teams and love turning complex concepts into actionable, data-driven results.

Felix Falkenberg

Full Stack Developer, Back-End Developer, Front-End Developer, +3

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Hi, I’m Felix Falkenberg — a DevOps & ML Engineer focused on bringing machine learning from prototype to production. I design and operate scalable, cloud-native ML platforms and microservices, with deep hands-on experience in Kubernetes, Docker, and AWS. With a background in psychology and a minor in computer science, I enjoy solving real-world problems in healthcare by translating research questions into robust models and data workflows. I thrive in cross-functional teams and love turning complex concepts into actionable, data-driven results.…Hi, I’m Felix Falkenberg — a DevOps & ML Engineer focused on bringing machine learning from prototype to production. I design and operate scalable, cloud-native ML platforms and microservices, with deep hands-on experience in Kubernetes, Docker, and AWS. With a background in psychology and a minor in computer science, I enjoy solving real-world problems in healthcare by translating research questions into robust models and data workflows. I thrive in cross-functional teams and love turning complex concepts into actionable, data-driven results.

Available to hire

Hi, I’m Felix Falkenberg — a DevOps & ML Engineer focused on bringing machine learning from prototype to production. I design and operate scalable, cloud-native ML platforms and microservices, with deep hands-on experience in Kubernetes, Docker, and AWS.

With a background in psychology and a minor in computer science, I enjoy solving real-world problems in healthcare by translating research questions into robust models and data workflows. I thrive in cross-functional teams and love turning complex concepts into actionable, data-driven results.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

DevOps & ML Engineer at Techniker Krankenkasse (Health Insurance), Hamburg

January 1, 2025 - October 7, 2025

Architected and deployed ML pipelines from prototyping through production implementation; advanced ML research using healthcare data; translated complex research questions into actionable statistical models; presented results with visuals; applied deep learning frameworks in Python and TensorFlow; implemented scalable services and infrastructure across microservices and data platforms; ensured production readiness via IaC, automated pipelines, and monitoring; managed ML microservices using Kubernetes and Docker; proficient with OpenShift, Kubernetes, ArgoCD, Terraform, Airflow, and GitOps; deployed cloud-native infrastructure on AWS (EKS, S3, Lambda, CloudWatch, IAM); designed scalable data pipelines; conducted project management for ML use cases.

Data Scientist at Techniker Krankenkasse (Health Insurance), Hamburg

April 1, 2020 - October 7, 2025

Advanced ML and Data Science research using healthcare data; translated research questions into actionable statistical models; presented results with clear visuals; applied deep learning methods and Python frameworks.

ML Engineer & DevOps at Techniker Krankenkasse (Health Insurance)

January 1, 2025 - October 7, 2025

Implemented and operationalized scalable services and infrastructure across microservices and data platforms. Ensured production-readiness through infrastructure-as-code, automated pipelines, and comprehensive monitoring. Orchestrated deployment, scaling, and maintenance of ML microservices using Kubernetes and Docker in production. Proficient in OpenShift, Kubernetes, ArgoCD, Terraform, Airflow, and GitOps methodologies. Deployed and managed cloud-native infrastructure and workloads on AWS (EKS, S3, Lambda, CloudWatch, IAM). Designed robust, scalable data pipelines for data processing and analysis. Led project management and requirements engineering for ML use cases.

Data Scientist at Techniker Krankenkasse (Health Insurance)

April 1, 2020 - October 7, 2025

Conducted ML research on healthcare data. Translated complex research questions into actionable statistical models. Built and evaluated models, presented results with clear visuals and data-driven solutions. Applied deep learning methods and frameworks (Python, PyTorch, Transformers) to healthcare problems and collaborated with clinical stakeholders.

ML Engineer & DevOps at Techniker Krankenkasse (Health Insurance)

January 1, 2025 - January 1, 2025

Architected and operationalized scalable ML pipelines, deploying production-grade ML services and end-to-end data processing pipelines. Led Kubernetes and Docker-based deployments, implemented infra-as-code, and built monitoring solutions. Worked across microservices, data platforms, and ML systems; familiar with OpenShift, ArgoCD, Terraform, Airflow, and GitOps. Used AWS (EKS, S3, Lambda, CloudWatch, IAM) for cloud-native workloads. Supported project management and requirements engineering for machine learning use cases.

Data Scientist at Techniker Krankenkasse (Health Insurance)

April 1, 2020 - April 1, 2020

Conducted advanced ML & data science research using healthcare data, translating complex research questions into actionable statistical models. Presented results with clear visuals and data-driven solutions to stakeholders.