Machine Learning Experts in Cologne
in minutes from over 15,000 CVs with the power of AI.Hire experts who can turn data into reliable models, build recommendation and forecasting systems, and integrate ML into production workflows. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Cologne, who have recently used Machine Learning
Hooman Behmanesh
Last position:
Fullstack Developer at Möbel Roller GmbH
- Further development of the existing e-commerce platform based on SAP Commerce (Hybris) to meet the growing demands of digital commerce.
- Ensuring the scalability and performance of the backend, so the platform remained stable and efficient even under heavy user load.
- Development and integration of new OCC REST APIs and services for modular extensions and flexible adjustments, to implement new features quickly.
- Optimization of data flows and interfaces, which significantly improved platform efficiency and system performance.
- Ensuring a maintainable and scalable code base by using Clean Code principles, proven design patterns, and a future-proof architecture.
- Reduction of errors through extensive testing with JUnit, Mockito, and load tests with Gatling, supported by the introduction of automated test processes.
- Improved system performance through targeted refactoring measures and efficient database queries, especially to handle peak loads.
- Use of modern cloud and monitoring tools such as Kubernetes, Google Cloud Platform (GCP), and Grafana to ensure a stable and monitored infrastructure.
- Clear improvement in efficiency, scalability, and reliability of the platform, which now meets the demands of a dynamic and growing e-commerce market.
Michael Kunz
Last position:
Enterprise Architect, Lead Architect of the transformation program and coach at Swiss Ministry
- Development of the overall architecture
- Support for the respective workstreams in developing architectures in the areas of infrastructure, data centers, security, and network topology
- Coordination of the architect pool
- Support for program management in building the transformation project based on agile methods
- Consideration of regulatory requirements for IT projects in the federal administration
Beshr Alnirabieh
Last position:
System Administrator – HealthCare IT & Data Infrastructure at Cellitinnen Hospital Association
- Integration of medical modalities (including ultrasound) into the existing IT infrastructure (DICOM, HL7) – put into operation within the planned timeframe.
- Administration and optimization of PACS systems for efficient archiving and distribution of radiology image data across multiple locations.
- Ensuring consistent data quality and seamless interoperability in data exchange between HIS, RIS, and PACS.
- Close collaboration with medical staff to analyze and digitally optimize clinical workflows.
- Requirements management and test coordination when implementing clinical requirements in complex IT structures.
Rodion Orlinskiy
Last position:
Founder, CTO & Managing Director at MYNR Product Mining GmbH
- Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
- Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
- Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
- Developed graph-based representations of product structures and dependencies for analytical reasoning.
- Designed and implemented an agentic AI framework for AI-supported decision workflows.
- Built scalable analytical microservices and integrated reporting through modern BI technologies.
- Coordinated backend, AI, and frontend development across the MYNR platform stack.
Fahad Razzaq
Last position:
Data Science – Operations Optimization at Netto-marken
Project: Digitalization of Warehouse Processes | Building a Data Analytics Platform.
- Built a web-based workforce allocation system that digitized daily shift planning by matching worker expertise to operational zones, replacing manual coordination with a structured workflow adopted across the site, saving supervisors time on daily planning.
- Developed a real-time operational visibility dashboard giving supervisors a live view of task throughput and outstanding workload across warehouse zones throughout the day, helping reduce overtime and idle labour costs.
- Developed a slotting optimization solution to improve warehouse picking efficiency and reduce picking time per order, working directly with operations teams from concept through production deployment.
Technologies used: Python, Django, PostgreSQL, Pandas, NumPy, HTML, Java, JavaScript, Docker, Kubernetes, AWS, Power BI, GitHub Actions CI/CD, GitOps, Claude, OpenAI
Muhammad Jamshaid Iqbal
Last position:
Embedded Linux Intern – IoT Sensor Prototype Development at DHL
- Built a modular C++ 20 embedded Linux acquisition system on a Raspberry Pi, synchronizing IMU and dual-camera data streams to sub-millisecond accuracy.
- Integrated retro-reflective and contrast sensors to trigger acquisition and detect gaps between sorter rails.
- Implemented SPI & I2C sensor communication, GPIO interrupt handling with libgpiod, and CSV & JSON output.
- Designed a multi-threaded acquisition pipeline and an SPSC queue between acquisition and writer threads.
- Built a Python/HTML/CSS based web-server and validated the prototype in a DHL warehouse for defect detection.
- Documented software behavior, configuration, and results for maintainable handover and further development.
Sophia Wagner
Last position:
AI Engineer & Technical Consultant at Freelance
- Delivered ML pipelines for OCR, semantic search, and computer vision
- Integrated Azure AI Agents and GPT workflows for automation and QA
- Deployed cloud-based FastAPI services with scalable architecture
- Created integration docs and advised on LLM production readiness
Emmanouil Tzouridis
Last position:
Senior Analytics Engineer at Trade Republic Bank GmbH
- Implementation of analytics and automation solutions for the Anti Financial Crime business unit
- Providing the infrastructure, including reusable data models and feature ingestion for production ML and rule based models in the areas of Account Take-Over and Card fraud detection, as well as Customer Risk Assessment
- Tools used: Snowflake, dbt, Looker, AWS, Python, Airflow, Metaflow
Markus Glagla
Last position:
Full Stack Developer at REWE Digital
- A warehouse valuation system was reimplemented using Java, Spring Boot, and Camunda. The backend solution focuses on integration and batch calculations, the frontend on managing formulas and reviewing results.
- Java 21
- Spring Boot
- JPA
- Maven
- REST
- Kafka
- PostgreSQL
- DB2
- Liquibase
- Google Cloud Storage
- Keycloak
- GitLab CI/CD
- Helm
- Terragrunt
- SonarQube
- Angular
- IntelliJ
- JUnit 5
- Mockito
- Open API
Kevin Baßler
Last position:
Procurator and AI Lead at ValueData GmbH
- Serve as AI lead for life-science solutions, integrating advanced AI models directly into company workflows and ensuring seamless deployment.
- Design and implement deep learning architectures (PyTorch, Keras) for complex biomedical challenges, including cell segmentation, multimodal omics analysis, and prediction of point clouds.
- Develop and deploy robust LLM-based systems, including RAG architectures and agentic workflows using LangGraph, to facilitate natural-language interaction with complex medical data.
- Lead cross-functional initiatives to apply foundation models and explainable AI (xAI) to clinical and evolutionary algorithms.
Dmitriy Drichel
Last position:
Freelance Senior Data Scientist at Merck KgaA
- AWS
- Genedata Profiler
- Data Lake
- APIs
- Rstudio
- GitLab
- Python
- R
- Data acquisition, integration, and simulation
- Multiplex immunofluorescence
- Copy-number variation calling
- HLA typing and loss-of-heterozygosity analysis
- RNA expression analysis
Abdulla Alshahri
Last position:
Senior Product Consultant (Contract) at Mindvalley
- Launched Eve AI, a conversational AI coach that increased course engagement by 25% through real-time, personalized prompts and guidance, reducing user isolation and improving user retention
- Led the development and beta release of the Transformation AI Coach, which provided tailored guidance to users, resulting in a 10% reduction in churn within the first quarter by utilizing predictive AI for personalized interventions
- Oversaw the rollout of AI-driven content recommendations across iOS/Android, boosting course completion rates by 25% through personalized suggestions based on dynamic user profiles
- Enhanced AI-driven customer experiences by optimizing predictive models for churn reduction, improving user retention with data-driven alerts and actions
- Spearheaded the use of predictive AI to analyze behavior and identify early churn risks, applying actionable prompts that directly impacted user retention and engagement
- Optimized AI-human escalation flows and maintained 90+ NPS while scaling engagement through smart feedback loops
Jeanne Yap
Last position:
Process Engineering Intern at Procter & Gamble
- Independently initiated and deployed automated validation workflows using Python, cutting manual processing by 58% and improving efficiency
- Developed a machine learning model for synthetic defect generation, reducing downtime and production costs; deployed locally and via Databricks and Azure AI Factory
- Utilized a small dataset of image data from the production lines and extended this dataset with training on models like cycleGAN and pix2pix
- Built and optimized the Linux-based development environment for training 3D models; maintained reproducibility via GitHub
- Presented technical insights to cross-functional teams (engineers, QA, project managers), ensuring alignment of ML solutions with operational needs
Jennifer Pütz
Last position:
Sales Development Manager at Uffective Germany
- Advised companies on implementing the SaaS solution for digital project and portfolio management by analyzing existing workflows and data flows
- Responsible for the entire B2B sales cycle: from lead generation and needs analysis to product demos, ROI justification, and contract closing
- Translated complex business requirements into technical solution concepts and coordinated with customer success teams
- Identified automation opportunities in customer processes and translated them into efficient software logic (workflows, rules, approvals, dashboards)
- Prepared and conducted executive readouts, including defining next steps, managing forecasts, and documenting projects
- Analyzed company data to identify opportunities for machine learning and automation scenarios to improve efficiency
- Worked closely with interdisciplinary teams to implement MS Office including MS Copilot PoCs and sustainable improvements in the customer environment
Hans Reinl
Last position:
Engineering and Leadership Consultant at Self-employed
Leveraging 15+ years of high-scale platform architecture and engineering leadership to consult with companies, focusing on enhancing their engineering capabilities and accelerating adoption of the AI-native web.
- AI & Machine Learning: Hands-on architecture and implementation using Vercel AI SDK, Next.js, Supabase, and Serverless architectures to build production-ready AI applications.
- Reference Architecture: Designed and implemented a full-stack, conversational coach (N+One AI Coach) based on Next.js and Vercel Edge Network for personalized training, demonstrating expertise in performant serverless applications and AI-powered experiences.
- Agentic Systems & Data Processing: Developed agentic-led, low-code crawling and indexing processes for fiber internet network information, showcasing proficiency in automation, LLM integration, and data structuring.
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
12 years (Germany: 14 years)
Position duration
1.7 years (Germany: 2.8 years)
Positions per freelancer
9 (Germany: 8)
Top business areas
Information Technology, Research and Development, Business Intelligence
Top industries
Information Technology, Education, Retail
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
86% (Germany: 77%)
Doctorate
19%
Certifications per freelancer
2
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
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 Cologne 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 Cologne using Machine Learning
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
What it covers
Machine learning turns data into models that learn patterns and make predictions or decisions. Companies use it for search ranking, fraud checks, forecasting, recommendations, anomaly detection, and natural language tasks. It sits behind many products that need to improve from data instead of fixed rules.
Common stacks
- Python, scikit-learn, TensorFlow, PyTorch, XGBoost
- Feature engineering, model training, evaluation, and tuning
- Data pipelines, experiment tracking, and model monitoring
- APIs and batch jobs that serve predictions in production
When to hire
Freelance specialists help when a team needs focused help on a model, a proof of concept, or a production rollout. They are also useful when internal teams know the data problem but need support with architecture, validation, or deployment. In Cologne, this often fits projects that need close work with product, data, and engineering teams.
What strong specialists do
Strong professionals work from clear business goals, not just notebooks. They define target variables, test baselines, watch for leakage and bias, and explain trade-offs in plain language. They also understand how to keep models stable after launch, which matters as much as the first result.
Project fit
Use machine learning when rules are too rigid and the system needs to adapt from examples. It suits structured data, text, images, audio, and event streams. Common deliverables include classifiers, ranking models, demand forecasts, and anomaly detection services.
Collaboration and tooling
A good engagement usually includes data access, reproducible training, and a plan for handover. In Cologne, some work is best done on-site when data access is sensitive or workshops are needed, while model building and review are often remote. Clear documentation, version control, and shared success metrics keep the work moving.
Frequently asked questions
Before you brief your next project: the most common questions about Machine Learning.
Machine Learning is used to build systems that learn from data and improve predictions, classifications, or rankings over time. Teams use it for recommendations, fraud detection, demand forecasting, anomaly detection, and text or image analysis. It is a good fit when fixed rules are not enough and the data can support learning.
A Machine Learning solution learns patterns from examples, while rule-based software follows instructions written by people. That makes ML better for messy data, changing behavior, and tasks where the logic is hard to spell out. Rule-based systems still win when the decision path must stay fully explicit and simple.
A strong Machine Learning specialist usually also knows data preparation, statistics, Python, SQL, and model evaluation. For production work, API design, cloud basics, containers, and monitoring are often needed too. The best fit depends on whether the project is a research prototype or a live system.
Not always, but the project should still be scoped well. A Machine Learning freelancer can help with data exploration, a baseline model, or a quick proof of concept even when the internal team is small. If the work touches production, sensitive data, or complex deployment, deeper experience matters quickly.
Bring in a Machine Learning freelancer when the need is specific, time-sensitive, or outside the team’s current focus. That is common for model reviews, feature work, prototype delivery, or support during a launch. It is also a practical option when the team needs extra expertise without a long hiring cycle.
Many Machine Learning tasks work well remotely, including data analysis, model training, code review, and documentation. On-site time in Cologne can help when access to internal systems is restricted or when workshops with stakeholders are important. A mixed setup is often the most practical choice.
Look for clear thinking about data quality, baseline methods, validation, and failure modes. A strong Machine Learning specialist can explain why a model works, when it will not, and how it should be monitored after launch. Good deliverables are reproducible, documented, and connected to a real business goal.
A Machine Learning engagement usually starts with the problem, the data, and the success criteria. Freelancers should expect to spend time on data cleanup, testing, model comparison, and communication with stakeholders. Good projects give access to the right data and clear ownership for deployment and maintenance.
The average hourly rate of freelancers in Cologne, Germany who have used Machine Learning in their recent projects is 96 €, which corresponds to a daily rate of about 770 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Machine Learning in their recent projects, 100% hold at least a Bachelor's degree, 86% hold at least a Master's degree, and 19% hold a doctorate.
On average, freelancers in Cologne, Germany who have used Machine Learning in their recent projects have 12 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Cologne, Germany who have used Machine Learning in their recent projects are German (100%), English (96%), and French (22%).
The most common industries among freelancers in Cologne, Germany who have used Machine Learning in their recent projects are Information Technology (78%), Education (61%), and Retail (43%).
The most common business areas among freelancers in Cologne, Germany who have used Machine Learning in their recent projects are Information Technology (87%), Research and Development (74%), and Business Intelligence (70%).
Main locations of FRATCH Experts, who have recently used Machine Learning
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 
Hamburg 
Munich 
Frankfurt 
Stuttgart 
Dusseldorf 
Dortmund 
Essen 
Bremen 
Dresden 
Hanover 
Nuremberg Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
