YAML Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used YAML
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Krithika Chand
Last position:
Professional Reorientation at Von Rundstedt
- Engaged in a structured career development program while strengthening German language proficiency (B1 level) and evaluating opportunities in ADAS/AD systems and requirements engineering.
Maziyar Khorrami
Last position:
Data Engineer at MSD Germany
- Lead Architect to design and implement the data lake and ETL Pipeline using AWS Stack
- Performance Optimization of Data Ingestion of ETL Pipeline
- Development of Data Validation using Great Expectations
- Leading of the data migration for two sources exchanges
- Data Modeling in AWS Redshift
MLOps
- Model inference implementation by mlflow and AWS SageMaker
- Feature Engineering for the running ML Models ( Recommender Engineer, Clustering )
- Implementatino of Model Registry and artifactory using mlflow
- Historization an Profiling of the Input Data Using AWS Glue Crawler and AWS Data Catalog
- Feature importance using mlflow
Tech. Stack: Python 3, AWS Glue, AWS Step Fucntion, AWS Lambda, AWS EventBridge, AWS IAM Role, AWS SageMaker, AWS EC2, AWS Glue Crawler, AWS CloudWatch, MLFlow, ETL, Data lake, GitHub Action, Terraform, Jenkins, Ansible playbooks (Infrastructure as Code), CI/CD, GitLab, SQL, PySparkSCRUM, Agile, Jira, BigData, VSCode, DBeaver, MSSQL, MySQL, grafana, Docker, Linux, Bash, MapReduce, Data Modeling (ORM), Pandas, YAML, SQL-Alchemy
Daniel Carton
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Daniel Redwig
Last position:
Software Engineer at DB InfraGO AG
- Developed dynamic web components for displaying KPIs, intelligent map applications, and operational process analysis tools
- Angular 18+
- Leaflet, MapLibre
- NestJS, JavaScript, HTML, CSS
- PostgreSQL, GraphQL, RabbitMQ
- Gitea, Jenkins, Docker
Bela Bocsak
Last position:
Full Stack Lead Developer, Backend Architect at Telefonica (O2)
The software supports the complete planning and approval of antennas for mobile telephony.
The system was implemented using an event-driven microservice architecture for cloud-native deployment with Quarkus on the backend, Kafka for communication, and Angular for the frontend. Services run on Kubernetes in Google Cloud. A special challenge was synchronizing with the legacy system still used by some users.
Valentin Pfeil
Last position:
Student in Cloud Engineering at IAV GmbH
- Container orchestration with Docker and Kubernetes clusters
- Operating cloud platforms like Rancher, Azure, and AWS
- Development with and use of infrastructure-as-code tools like Terraform, Kubectl, and Helm
- Analysis and use of Python, YAML, and JSON
Janusz Mazurek
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Dominik Arnoldi
Last position:
IUeIvnOteprsnEatnigoinnaeleerHForechelsacnhcueler GmbH
- Migrated DataRobot into existing infrastructure
- Created AI infrastructure on AWS
- Migrated Bitbucket pipelines to GitLab
Discover over 15,000 top freelancers
Statistics of experts using YAML
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 18 years)
Position duration
2.2 years (Germany: 1.9 years)
Positions per freelancer
12 (Germany: 13)
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Automotive, Banking and Finance
Bachelor's degree or higher
100% (Germany: 95%)
Master's degree or higher
100% (Germany: 64%)
Doctorate
29% (Germany: 13%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 99%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Munich using YAML
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
YAML in practice
YAML is a human-friendly format for structured data and configuration. Companies use it for application settings, infrastructure definitions, build pipelines, and deployment manifests. It is common in Docker, Kubernetes, GitHub Actions, and many cloud and DevOps workflows.
Where it appears
- Kubernetes manifests and Helm values
- CI/CD pipelines and release workflows
- Application and service configuration
- Infrastructure and automation files
- Data exchange between tools and services
What strong experts do
Strong YAML professionals keep files readable, consistent, and safe to change. They know indentation rules, anchors, aliases, multiline strings, and common schema patterns. They also understand how YAML is interpreted by each tool, because the same file can behave differently across systems.
Tooling and ecosystem
YAML work often sits next to Docker Compose, Kubernetes, Helm, Ansible, GitHub Actions, GitLab CI, and cloud templates. Skilled specialists validate files, catch indentation mistakes early, and keep configuration aligned with the surrounding toolchain. In Munich, this often matters for teams running modern product, platform, or cloud operations.
When companies bring in freelancers
Companies usually bring in freelance YAML experts when configuration becomes hard to trust, review, or extend. Typical cases include migration between environments, cleanup of large manifest sets, pipeline refactors, or support for a new platform standard. Teams also ask for help when internal experts are busy and delivery cannot wait.
What quality looks like
Good YAML is not just valid. It is clear, consistent, and easy for other specialists to review. Strong freelancers document assumptions, reduce duplication with reusable structures where it helps, and check the files against the target system so the result works in practice, not only in syntax checkers.
Frequently asked questions
Everything clients usually want to know about YAML, in one place.
YAML is used for configuration, deployment manifests, automation, and structured settings that humans need to read and edit. In practice, it shows up in Kubernetes, Docker Compose, CI/CD pipelines, and many cloud tools. Companies hire specialists when those files control important environments and need to stay reliable.
YAML is usually chosen when readability matters and people need to edit files by hand. JSON is stricter and often simpler for machines, while XML is more verbose and better suited to some legacy or document-heavy systems. A good freelancer knows when YAML is the right fit and when another format is safer.
A strong YAML specialist usually understands the target tools as well, not just the syntax. For platform work, that often means Kubernetes, Helm, Docker Compose, GitHub Actions, GitLab CI, or Ansible. They should also be comfortable with Git, code review, and configuration testing.
YAML work needs enough context to know which system will read the file and what behavior it controls. A small config cleanup can be straightforward, but deployment manifests or pipeline files need a clear view of the environment, naming rules, and rollout process. The best results come when the specialist can read the surrounding toolchain, not only the file itself.
Bring in a YAML freelancer when the team has a backlog of brittle configs, repeated indentation errors, or a migration that touches many files. It also helps when you need a fresh review before a release, or when internal specialists are focused on product work. The value is speed, clarity, and fewer mistakes in critical automation.
Most YAML work can be done remotely because the core tasks are reviewing files, checking tool behavior, and aligning with the team in code. On-site time in Munich can still help during workshops, incident reviews, or fast-moving migrations with many stakeholders. The right choice depends on how much coordination the project needs.
A good YAML expert writes files that are easy to read, consistent across environments, and valid for the target system. Look for clean structure, careful use of anchors and aliases, and a habit of testing against the real tool, such as Kubernetes or a CI pipeline. Clear communication and disciplined version control are also strong signs.
The most common YAML problems are indentation errors, unclear nesting, overuse of duplication, and files that work in one tool but fail in another. Another issue is treating YAML as only a syntax task instead of checking the full workflow around it. Skilled specialists prevent these problems by reviewing both content and context.
The average hourly rate of freelancers in Munich, Germany who have used YAML in their recent projects is 110 €, which corresponds to a daily rate of about 880 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used YAML in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 29% hold a doctorate.
On average, freelancers in Munich, Germany who have used YAML in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Munich, Germany who have used YAML in their recent projects are German (100%), English (89%), and Spanish (11%).
The most common industries among freelancers in Munich, Germany who have used YAML in their recent projects are Information Technology (100%), Automotive (56%), and Banking and Finance (44%).
The most common business areas among freelancers in Munich, Germany who have used YAML in their recent projects are Information Technology (100%), Product Development (78%), and Project Management (56%).
Main locations of FRATCH Experts, who have recently used YAML
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Cologne Request a free demo
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Philipp Thomaschewski
FRATCH CEO
