Machine Learning Experts in Düsseldorf
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Meet FRATCH Experts in Düsseldorf, who have recently used Machine Learning
Alwin G.
Last position:
IT Interim Manager & AI Strategist
- AI product development: Design of an AI-supported GRC platform to automate compliance processes.
- AI expertise: Strategic deepening in Agentic AI and GenAI as a core asset for modern IT governance
- IT interim management and strategic consulting
Boris Solos
Last position:
Generalist expert for software development at Mercor
- Training the AI models, evaluating images and texts for UI/UX, turning the provided data into insights via OpenAI Feather as part of the machine learning workflow
Technologies: OpenAI Feather
Dr Daniel Steinberg
Last position:
Director of Partner & Alliances, AI Use Cases, EMEA at Teradata Deutschland GmbH / Teradata Corporation EMEA
- Define EMEA ISV Go-to-Market strategy to push indirect SaaS sales
- Solve customer problems with AI embedding into new use cases and solutions
- Build partner ecosystem and sell partner solutions to drive platform consumption
- Enable cross-functional teams on AI use cases implementation
- Manage a cross-functional team of 7 FTE
- Built EMEA partner originated pipeline from scratch with 70 mn€ TCV and 20 mn€ ARR growth sales with cloud-based and hybrid solutions
- Increased co-sell rate from 20% to 40% and co-delivery rate from 25% to over 50%
Chenchen Chu
Last position:
Patent Engineer (European patent attorney candidate) at Vossius & Partner
- Patent application: European patent drafting and prosecution
- LLM practicing: Developed LLM-based tools for automated patent data retrieval, applying Python scripting to accelerate technical reviews.
Hans-Dieter Große-Kreul
Last position:
Training as an AI Expert
I continuously expand my expertise in AI and automation, working with ChatGPT, OpenAI, Manus, Gemini, MS CoPilot, API, LangChain, Hugging Face, Manus, TensorFlow and Auto-GPT as well as Python-based ML frameworks and MLOps tools to intelligently transform classic software development, analysis, and testing processes.
Ehsan Amin
Last position:
Clinical Data Scientist at Freelance
- Conduct data management and statistical analysis for clinical studies on behalf of CROs.
- Guest lecturer at Ivancity University, Paris, specializing in data anonymization techniques and statistical disclosure control.
- Provide scientific and medical writing services for pharmaceutical companies.
- Perform optical mapping data analysis and develop software tools with a focus on algorithm optimization and technical support.
Peter Pries
Last position:
CRM & Bid Management Project Consultant at Global mechanical engineering company
- CRM process and feature consulting
- AI infusion workshops to introduce AI apps for critical business processes
- Prototyping – Vibe coding with Lovable
- Development of several apps for global bid management in the CPQ, Salesforce, and SAP S/4HANA environment
- Requirements and process management
- Introduction of a new data governance model
- AI infusion – supporting apps and business processes with AI applications
- Portfolio management of AI ideas: identifying and selecting AI projects in bid management
- Prototyping AI projects with Lovable.dev
- Building an AI data foundation in Snowflake
- Blueprint for different business units and global rollout
- An agile prototype-first approach with design thinking and vibe coding to prototype all applications
- Presentation at a global conference on using AI in business and validating ideas with design thinking & vibe coding
- AI infusion workshops at global conferences for prototyping ideas with business stakeholders
Mohammed Elgazzar
Last position:
Interim CTO & Senior Tech Consultant at ASCEND gGmbH / RepairX.io / GHBIO.org
- Development of the SmartHub platform for RepairX.io (iOS app & web)
- Development of an AI-powered (clinical decision support) patient management platform for the Malteser Hospital to provide care for uninsured patients
- Development of a retrieval-augmented generation (RAG) system for the intelligent processing of medical data for ASCEND gGmbH
- Design of an AI-powered system for emotion analysis of guests and development of AI agents for automated accounting and compliance checks
- Planning of the RepairX.io platform (circular economy) and management of a DAO Hyperledger blockchain system for NGOs
- Development of internal audit systems for AI ethics violations in healthcare (according to the EU AI Act)
Mitali Soti
Last position:
Freelancer at Fintom8 Fintech AI UG
- Built and launched the AI-powered “E-Invoice Corrector,” an intelligent system for validating and correcting invoices, using Python, FastAPI, and machine learning. The system is now live at Fintom8.
- Converted the Corrector into a fully functional API, published with Swagger documentation for easy access and integration by internal and external consumers.
- Designed, experimented with, and optimized advanced LLM prompts and meta-prompting strategies to improve automated reasoning, error correction, and decision-making in agent workflows.
- Wrapped and integrated existing APIs within the Google Agent Development Kit (ADK) framework to enhance automation capabilities and conversational AI workflows.
- Implemented comprehensive unit testing using pytest and unittest, and employed breakpoint debugging (VS Code, pdb) to ensure code reliability, maintainability, and smooth runtime execution.
- Utilized Pydantic and Tabulate for structured data validation, API schema management, and clear tabular data representation in testing and debugging workflows.
- Pursuing the Google Cloud Professional Certificate.
Aziz Ajrir
Last position:
Senior Data Scientist & AI Engineer Consultant at Lialab SAS
- At Groupama: Developed multiple chatbots using Retrieval-Augmented Generation (RAG) to optimize internal processes and customer communication.
- At PwC: Set up an AI lab and developed various AI use cases.
- At La Poste: Analyzed and improved data quality in the data lake.
- At ARTE TV: Built a recommendation system using NLP for better content discovery.
Dalia Cananau
Last position:
Oracle Developer at Freelance
- Design and implementation of an OCI-based data warehouse and ETL system to replace legacy mainframe applications
- Developed a database optimization strategy and planned the rapid conversion of JCL and COBOL routines to PL/SQL using AI
- Developed an Oracle Apex-based app for internal administrative processes in the public sector (office equipment, staff training)
- Implemented PL/SQL workflows for approval processes and created a responsive mobile version with JavaScript and CSS
- Used Azure DevOps for backlog management and documentation, and Git for version control
- Developed REST interfaces to CRM systems
- Replaced and reprogrammed Oracle Forms screens with Oracle Apex and updated to the latest Apex versions
- Designed a Git branching strategy and conducted code reviews
- Maintained and further developed an EDI-based data exchange system based on Oracle Advanced Queuing for the public sector in Austria
- Performed data analysis and created charts in the Oracle Apex frontend; installed standalone ORDS and Apex 23.1
- Worked agile using the Spotify model; developed complex Apex pages with support from Oracle JET
- Rebuilt and customized existing PL/SQL packages, created workarounds for database version differences, and optimized queries
- Developed Apex applications for broker pools to manage and optimize Oracle databases in the banking environment, including SSO-based authorization systems with OAuth2 and Keycloak
- Built extensive Oracle Apex applications for BI and data mining modernization projects and developed manual and automated projection methods in the frontend
- Carried out data warehousing projects in the banking sector and used Scrum and Kanban in team projects
Rüdiger Kohl
Last position:
Data Analyst and Reporting Manager at Energieversroger
Implemented Power BI reporting for various departments at an energy provider. Agile project: responsible for organizing and coordinating with departments and IT, and regularly presented interim steps and results to project management.
Jörg Nieveler
Last position:
Senior Software Architect at Nieveler IT Consulting
- Redesign of the 'Hessian Platform for Migration and Refugees'
- Technologies: C#, .NET 8.0, ASP.NET WebAPI, Blazor
- Architecture principles: Domain Driven Design, Mediator Pattern, Outbox Pattern, IOSP, Clean Code
- Methodologies: SCRUM, Coaching, Team Lead
Simon Stegelmeier
Last position:
Cloud Data Platform Product Owner & Project Manager at Mediengruppe RTL Deutschland
- Communication between B2B & B2C product platforms
- Stakeholder management
- Monitoring
Sara Welter
Last position:
Recruiting & Employer Branding Data Specialist at Sipgate
- Managed the entire hiring process with a focus on data-driven decision-making.
- Analyzed recruiting data using Excel and ATS to optimize processes effectively.
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
18 years (Germany: 14 years)
Position duration
2.2 years (Germany: 2.8 years)
Positions per freelancer
12 (Germany: 8)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Manufacturing, Banking and Finance
Certification focus areas
Information Technology, Project Management, Research and Development
Bachelor's degree or higher
87% (Germany: 97%)
Master's degree or higher
67% (Germany: 77%)
Doctorate
27% (Germany: 19%)
Certifications per freelancer
3 (Germany: 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 Düsseldorf 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 Düsseldorf 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 helps systems learn from data and improve at tasks such as prediction, classification, ranking, and anomaly detection. It sits at the core of recommender systems, forecasting tools, search relevance, fraud signals, and many decision-support products. Teams often call it ML when they speak about the same work.
Typical work
- Model training and evaluation
- Feature engineering and data preparation
- Prediction APIs and batch scoring
- Recommender and ranking logic
- Monitoring for drift and quality
Tools and stack
Strong professionals working with Machine Learning usually know Python, SQL, pandas, scikit-learn, TensorFlow, PyTorch, and notebooks. They also understand data pipelines, version control, experiment tracking, and cloud services used to run training jobs and serve models. The right stack depends on the data and the delivery target.
When to bring in help
Companies often look for freelance support when a model must move from proof of concept into a stable product, or when an existing ML system needs cleanup. This is common in Düsseldorf for logistics, retail, finance, industrial, and media use cases where data is complex and delivery must stay practical. It also helps when teams need extra hands for short, focused work.
What strong experts do
Good experts do more than tune models. They question the data, check the label quality, design sensible baselines, and explain trade-offs in a way product teams can use. They also write code that can be maintained, tested, and deployed without guesswork.
What to expect locally
In Düsseldorf, many projects need both remote cooperation and some local availability for workshops, stakeholder sessions, or data access discussions. Clear communication in English is common, and German can help when work touches internal teams or local business processes. The best specialists adapt to the way your team already works.
Frequently asked questions
Before you brief your next project: the most common questions about Machine Learning.
Machine Learning is used to turn data into predictions, rankings, classifications, and automated decisions. Companies use it for demand forecasting, fraud signals, recommendations, anomaly detection, and document or image analysis. The best results come when the model fits a real business process, not just a demo.
Machine Learning is better when rules are hard to write because the patterns are noisy, changing, or hidden in data. Rule-based systems are often easier to explain, while ML can adapt to complex inputs such as text, images, or user behavior. Many teams use both together: rules for guardrails and models for prediction.
ML is a part of AI, but not the whole field. AI includes broader ideas such as planning, reasoning, and language systems, while machine learning focuses on learning patterns from data. If a company asks for ML work, it usually means modeling, data prep, evaluation, and deployment.
A strong Machine Learning specialist usually brings Python, SQL, statistics, data cleaning, and solid software practices. Knowledge of feature engineering, experiment design, and cloud deployment matters as much as model choice. For production work, MLOps, monitoring, and versioning are often essential.
A machine learning project works best when the expert gets access to the business goal, the data sources, the target label, and the current pain points. Without that context, it is easy to build a model that looks good in isolation but fails in use. A short discovery phase often saves time later.
Yes, Machine Learning work is often remote because most tasks live in code, notebooks, and data pipelines. For teams in Düsseldorf, remote collaboration works well for model development, review, and delivery, while a local or on-site presence can help with workshops or sensitive data access. The right setup depends on the project phase.
Look for clear problem framing, strong data checks, and the ability to explain why a model should be trusted. A good Machine Learning specialist shows evidence of deployment, monitoring, and maintenance, not only training results. They should also be honest about limits, data gaps, and risks.
Freelancers working with Machine Learning usually ask about the data quality, the success metric, the deployment path, and who owns the product decision. They also want to know whether the work is research, prototype, or production support. Clear answers help them estimate the effort and choose the right approach.
The average hourly rate of freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects is 91 €, which corresponds to a daily rate of about 730 € based on an 8-hour working day.
Of the freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects, 87% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 27% hold a doctorate.
On average, freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects are German (100%), English (100%), and French (47%).
The most common industries among freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects are Information Technology (71%), Manufacturing (53%), and Banking and Finance (47%).
The most common business areas among freelancers in Dusseldorf, Germany who have used Machine Learning in their recent projects are Information Technology (88%), Product Development (88%), and Business Intelligence (53%).
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 
Cologne 
Frankfurt 
Stuttgart 
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.
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We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
