YAML Experts in Munich
to shape reliable configuration with vetted, available freelancers matched by AIHire experts who create maintainable configuration for Kubernetes, CI/CD pipelines, cloud infrastructure and application deployments. FRATCH matches you quickly and precisely with vetted, available freelancers who fit your YAML requirements.
Meet FRATCH Experts in Munich, who have recently used YAML
Michael N.
Last position:
Senior AI Engineer | Forward Deployed Engineer at Tiefbau
- Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
- Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
- Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.
Krithika C.
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.
Daniel R.
Last position:
Software Engineer at DB InfraGO AG
- Development of 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
Maziyar K.
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 C.
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)
Bela B.
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 P.
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 M.
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 A.
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 19 Sep 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
YAML experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (100%)
- Automotive (56%)
- Banking and Finance (44%)
- Manufacturing (44%)
- Professional Services (44%)
- Government and Administration (44%)
- Telecommunication (44%)
- Education (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Configuration Language
YAML is a human-readable data serialization language used to express configuration and structured data. Its indentation-based syntax is common in application settings, deployment manifests, automation files and data exchange. YAML files usually use the .yaml or .yml extension.
Where It Runs
YAML appears across modern software delivery and cloud environments. It defines Kubernetes resources, Docker Compose services, GitHub Actions workflows, GitLab CI pipelines, Ansible playbooks and configuration for tools such as Helm and Azure DevOps. It also supports application configuration in many programming ecosystems.
Core Expertise
Strong YAML specialists understand more than indentation and key-value pairs. They work with anchors, aliases, sequences, mappings, multiline strings, environment substitution and schema validation. They also know how YAML is interpreted by the specific tool consuming the file, since implementation details can differ.
Typical Deliverables
- Kubernetes manifests and Helm values
- CI/CD workflow definitions
- Docker Compose and service configuration
- Ansible inventory and playbook files
- Validated application and environment settings
Well-structured files make deployments easier to review, reproduce and troubleshoot. Specialists may also create templates, reusable conventions and validation rules for teams managing configuration across environments.
When to Hire
Companies bring in freelance YAML expertise when configuration has become difficult to maintain or deployments behave differently between environments. A specialist can refactor duplicated files, resolve parsing and schema errors, introduce safe templating, or prepare Kubernetes and pipeline configuration for a new service. In Munich, remote collaboration is often practical, while on-site workshops can help align product, operations and security teams.
Quality Signals
Good YAML work is clear, valid and suited to the tool that reads it. Experienced professionals use linters, schema checks, format validation and pipeline tests instead of relying on visual inspection alone. They document assumptions, keep secrets out of repositories, handle environment differences deliberately and explain the trade-offs behind reusable configuration. German or English documentation can be arranged to fit the project team.
Frequently asked questions
Everything clients usually want to know about YAML, in one place.
YAML is mainly used for configuration and structured data. Companies use it for Kubernetes manifests, CI/CD workflows, Docker Compose files, Ansible automation, Helm values and application settings.
YAML is generally easier for people to read and supports comments, multiline values and expressive structures. JSON has stricter syntax and broad interoperability, while TOML is often simpler for smaller configuration files; the right choice depends on the consuming tool and validation needs.
A strong YAML specialist usually understands the ecosystem around the files, such as Kubernetes, Helm, Docker, Ansible, Git and CI/CD systems. Knowledge of shell scripting, cloud services, secrets management and schema validation is also useful because YAML rarely works in isolation.
The required depth depends on the scope. Editing a small configuration file may need general YAML knowledge, while designing reusable Kubernetes manifests or multi-environment pipelines calls for practical experience with the relevant platform, deployment process and failure modes.
YAML projects are often well suited to remote collaboration because files, reviews and validation runs can be shared through version control. Teams in Munich may still prefer on-site sessions for architecture workshops, release planning or coordination across German- and English-speaking stakeholders.
YAML is sensitive to indentation and can produce confusing results when values are implicitly typed or formatted unexpectedly. Duplicate keys, incorrect nesting, invalid schema fields, unsafe secret handling and differences between parsers are common issues that validation and automated tests can catch.
Review whether YAML files are valid, readable, consistently structured and correct for the tool consuming them. Ask for evidence of linting, schema checks, automated deployment tests, clear environment handling and documentation that helps another professional maintain the configuration.
YAML can support large systems when files are modular, validated and governed by clear conventions. Templates, overlays, reusable fragments and schema checks help control complexity, but teams should avoid deeply nested structures and hidden dependencies that make changes hard to review.
The average hourly rate of freelancers in Munich, Germany who have used YAML in their recent projects is 111 €, which corresponds to a daily rate of about 888 € 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 (67%).
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
