Machine Learning Experts in Dortmund
to turn data into working products, matched in minutes with vetted and available freelancersHire experts who build predictive models, recommendation systems and computer vision workflows with Python, scikit-learn, TensorFlow and cloud data platforms. FRATCH matches you quickly and precisely with vetted, available freelancers suited to your project.
Meet FRATCH Experts in Dortmund, who have recently used Machine Learning
Laurin H.
Last position:
Software Architect (Freelance) at Care4Sure
- Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
- Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.
Ashwin P.
Last position:
Freelance Data Scientist at Mercor Intelligence
- Architected and deployed end-to-end machine learning pipelines across classification and prediction datasets, ensuring robustness and reproducibility through MLOps best practices.
- Contributed directly to LLM model output accuracy improvement by designing and engineering specialised prompts grounded in end-to-end ML and SciML pipeline logic.
- Developed training data for large language models by formulating coding problems that models could not resolve and subsequently documenting the correct solutions.
Daniel F.
Last position:
AI Researcher & LLM Evaluation – Conventional Paradigm Test (CPT) at Private
Conventional Paradigm Test (CPT) – AI Evaluation & LLM Research
Development of an experimental evaluation approach to examine “paradigmatic closure” in Large Language Models — that is, the question of how far LLMs can recognize the basic assumptions, values, and limits of the paradigms within which they generate answers.
Design and testing of an additional approach to classic AI benchmarks that does not primarily measure factual correctness or task performance, but instead examines a model’s ability to recognize alternative perspectives, make implicit assumptions visible, and reflect on the limits of its own answer or interpretation framework.
Focus areas: development of evaluation criteria and test questions · LLM evaluation and comparative model analysis · prompt and response analysis · qualitative classification of model answers · study of epistemic compression and value leakage · benchmark and literature research · development of structured assessment and analysis methods
As part of CPT, existing AI evaluation approaches and benchmarks were analyzed, and a minimalist test protocol was developed that classifies model answers by response patterns such as DIRECT, CLARIFY, PLURALIST, REFUSE, and META-AWARE. TruthfulQA was used as the basis for experimental application and comparison with existing reference answers.
Technologies & Methods: Large Language Models (LLMs) · Generative AI · Prompt Engineering · AI Evaluation · TruthfulQA · Benchmark Analysis · Human-in-the-Loop Evaluation · Qualitative Content Analysis · Research & Literature Review
Dany-Armand D.
Last position:
Senior Data Scientist at ibg NDT GmbH
- Investigate the relationship between Eddy Current Testing (ECT) signals and microstructural properties
- Detect latent patterns in ECT data that reflect intrinsic material characteristics
- Develop and validate predictive models for microstructural classification and quantification, using hardness and case depth as benchmarks
- Apply Bayesian Structural Equation Modeling for advanced data analysis
Patrik G.
Last position:
Technical Lead Conversational AI at CANCOM
- Technical lead of a team developing agentic chatbot solutions (React, TypeScript, Python, FastAPI)
- Architecture design for multi-LLM dialog systems - focus on maintainability, UX, and autonomous execution
- Stakeholder alignment, CI/CD processes, and AI integration at enterprise level
Derek M.
Last position:
AI Automations Manager - Hardware Setup, Automation & Voice Agent at Autohaus Mazda
- Setting up new desktop computers
- Setting up a VPS for automation, databases and chat interface
- Connecting to Azure AI Foundry
- Developing various n8n workflows for email, social media and document management
- Implementing a QA system (backups, error handling, HITL)
- Setting up and optimizing an inbound voice agent
Christian W.
Last position:
Interim Business Analyst / Product Owner at Bundesdruckerei GmbH (via FourEnergy GmbH)
- Initial assessment of requirements based on a business value prioritization framework
- Identification of issues as well as requirement gathering and evaluation using UML, BPMN, and design thinking methods for iterative requirements analysis through interviews and workshops
- Use of user story mapping in Miro to visualize and align functional requirements (e.g. correct transmission of all application data and attachments to the specialist system) as well as non-functional requirements (e.g. complete and verifiable deletion of an applicant's data) with stakeholders
- Proactive stakeholder management of internal and external stakeholders from public authorities, business units, organizations, and companies
- Preparation of status reports to communicate project progress and upcoming tasks transparently
- Responsibility for a REST-based integration solution (middleware) for secure data exchange between core systems and external specialist applications; ensuring stability and performance in day-to-day operations
- Support for Product Owners in prioritizing backlog items and in product discovery
- Communication of planning to internal and external stakeholders as well as interim assumption of Product Owner tasks and responsibilities during a staff change
Mesut Y.
Last position:
Solution Architect Computer Vision Store at Schwarz IT (Lidl/Kaufland)
- Expansion and support of the product portfolio for video analytics and computer vision
- Requirements gathering and engineering
- Consulting, project management and coordination of the pilot and international rollout
- Tools: IP-based camera and video systems, Citrix administration, OneNote, Microsoft Teams, Node-RED, Office 365, Age Verification, Qognify Umbrella, ThingsBoard, Xovis 3D sensors, AXIS cameras, GK checkout software, Atlassian JIRA
Andreas E.
Last position:
AI Coach and Consultant at Studio 8 Dortmund
- Setting up and consulting a startup for organizational development (AI-supported)
- Vision and mission workshops
- Marketing roadmap and process design
- Development of sales processes (sales funnel, lead generation)
- Brand building and social media omnichannel strategies
- Content generation for audio, video, and posts (AI-supported)
- Agile consulting and SAFe implementation
- Atlassian consulting and setup of Confluence and Jira (workflows, dashboards, reporting)
- Setup of a podcast and video studio including live streaming setup
- Selection and implementation of hardware and software
- Website creation and brand building
- CMS implementation based on Typo3
- Consulting in sales, marketing, and social media
- Supporting companies in the efficient use of AI technologies
- Strategy development and consulting on implementing AI strategies
- Change management and supporting teams in AI adoption, including training
- Technical expertise in machine learning, data processing, and large language models (LLMs) like Llama, Claude, and OpenAI GPT
- Selection, fine-tuning, and integration of LLMs into business processes
- Consulting on ethics and governance for responsible AI use
- Conducting tailored training for executives and teams
- AI analysis of various large language models (Llama, OpenAI, Mistral)
- Creation and training of custom GPTs focused on organizational development (product vision, OKR, agile maturity)
- Development of a chatbot on agile maturity
- Development of an AI-generated survey to assess organizational agility
- Setup of local offline GPTs with a focus on data protection and GDPR compliance
- Conducting AI workshops for SMEs and mid-sized companies
Hendrik B.
Last position:
Lecturer at Front and Fullstack Development Lecturer
- Teaching JavaScript, HTML, CSS, React, NodeJS, MongoDB, MariaDB, and Express
- Designing and preparing lessons
- Classroom teaching and one-on-one coaching
Rosemarie F.
Last position:
Freelance Management Consultant in the Construction Industry at Freelance Management Consultant
- Implemented Agile methodologies to drive AI-enabled process optimization
- Integration of AI-driven solutions with SAP S/4 HANA
- Facilitated the adoption of advanced analytics tools to enhance decision-making
Mohammed A.
Last position:
Data Scientist & Energy Consultant at Accenture GmbH
Ilja L.
Last position:
Software Engineer/Architect (Tech Lead) at Mercedes-Benz Tech Innovation GmbH
- Implementation of various interfaces for subsystems and connection to external devices (cameras, scanners, digital lockers)
- Development of various interfaces in the used cars area
- Realization of various prototypes
- Support in UI/UX and data analytics
- Development of frontend and backend solutions
- Kubernetes migration
- Building CI/CD pipelines
- Communication with the business unit and technical design of new solutions
- Cross-team alignment and coordination within the team
- Overview of the entire technology stack and related systems
- Documentation, preparation, and conducting of reviews
- Supporting the team and coordinating releases and key milestones
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
2.7 years (Germany: 2.8 years)
Positions per freelancer
11 (Germany: 9)
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
91% (Germany: 97%)
Master's degree or higher
45% (Germany: 77%)
Doctorate
27% (Germany: 18%)
Certifications per freelancer
4 (Germany: 2)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
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 Dortmund 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 Dortmund 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Machine Learning 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 (77%)
- Education (69%)
- Healthcare (62%)
- Professional Services (62%)
- Automotive (46%)
- Manufacturing (46%)
- Energy (38%)
- Retail (38%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Machine Learning does
Machine Learning enables software to learn patterns from data and produce predictions, classifications or recommendations without relying on fixed rules for every case. Teams use it for demand forecasting, fraud detection, document processing, search, personalization, industrial inspection and natural language applications.
Models and data
A reliable project starts with useful data, a clear target and a method that can be tested in production. Experts prepare datasets, define features, select suitable algorithms and compare results against a meaningful baseline.
- Classification, regression and clustering
- Time-series forecasting and anomaly detection
- Recommendation, ranking and similarity models
- Computer vision and text processing
Tools and ecosystem
Python is the common working language, with pandas and NumPy for data preparation and scikit-learn for established modelling workflows. TensorFlow and PyTorch support neural networks, while tools such as MLflow, notebooks, Docker and cloud services help teams track, package and operate models.
When companies need expertise
Freelance specialists are useful when an internal team has valuable data but lacks capacity to turn it into a dependable product. They can clarify feasibility, repair a weak modelling pipeline or bring a prototype into production.
- Establishing data quality and labelling processes
- Designing training, validation and evaluation workflows
- Improving inference speed, robustness or explainability
- Connecting models to APIs, applications and business systems
Production and operations
A model is only valuable when it keeps working after deployment. Strong professionals address feature pipelines, model versioning, monitoring, drift, reproducibility, access control and retraining, then document how results should be interpreted and maintained. In Dortmund, remote collaboration can work well, while on-site workshops may help when projects involve factories, logistics or other physical operations.
Choosing the right specialist
Look for evidence of complete Machine Learning delivery, not only attractive experiments or benchmark scores. A capable expert can explain trade-offs in plain language, challenge unreliable assumptions and connect technical choices to business outcomes. Ask how they handle missing data, changing patterns, biased samples, privacy constraints and model failure in live systems. Experience with software delivery, cloud infrastructure and stakeholder communication is often as important as modelling knowledge.
Frequently asked questions
Curious about Machine Learning? Here are the answers that come up again and again.
Machine Learning is used to predict demand, detect unusual activity, classify documents, recommend products, inspect images and automate language-based workflows. The best use cases have a clear decision to improve and enough relevant data to support it.
Machine Learning learns relationships from examples, while rule-based software follows logic written directly by people. It is useful when patterns are complex or change over time, but it needs careful data preparation, evaluation and monitoring.
Machine Learning is the broad field, and deep learning is one group of methods within it. Generative AI focuses on creating content, whereas many business problems are better served by a smaller predictive or classification model that is easier to test and operate.
A strong Machine Learning expert often combines modelling with Python, SQL, data engineering, statistics and software development. Experience with APIs, cloud infrastructure, Docker, model monitoring and responsible data handling can make the difference between a promising experiment and a usable service.
The right level depends on the project’s data quality, risk and production scope rather than on a fixed experience threshold. For an exploratory model, a specialist who can validate assumptions may be enough; regulated or business-critical systems require proven delivery, monitoring and documentation skills.
Machine Learning work is often well suited to remote collaboration because data, notebooks, repositories and cloud environments can be shared securely. On-site sessions in Dortmund may still be valuable for understanding factory processes, logistics operations, laboratory work or stakeholders who need direct workshops.
Assess whether the Machine Learning specialist can define a useful baseline, prevent data leakage and select evaluation methods that reflect real usage. Ask for a clear explanation of error analysis, deployment plans, monitoring and how the model behaves when data changes.
Before engaging a Machine Learning professional, clarify the business decision, available data sources, access restrictions and how success will be evaluated. A specialist can then determine whether modelling is appropriate, identify gaps in the data and propose a practical path from discovery to production.
The average hourly rate of freelancers in Dortmund, Germany who have used Machine Learning in their recent projects is 95 €, which corresponds to a daily rate of about 757 € based on an 8-hour working day.
Of the freelancers in Dortmund, Germany who have used Machine Learning in their recent projects, 91% hold at least a Bachelor's degree, 45% hold at least a Master's degree, and 27% hold a doctorate.
On average, freelancers in Dortmund, Germany who have used Machine Learning in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.7 years.
The most common languages among freelancers in Dortmund, Germany who have used Machine Learning in their recent projects are German (100%), English (100%), and French (23%).
The most common industries among freelancers in Dortmund, Germany who have used Machine Learning in their recent projects are Information Technology (77%), Education (69%), and Healthcare (62%).
The most common business areas among freelancers in Dortmund, Germany who have used Machine Learning in their recent projects are Information Technology (92%), Product Development (92%), and Research and Development (92%).
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 
Dusseldorf 
Essen 
Bremen 
Dresden 
Hanover 
Nuremberg Request a free demo
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FRATCH CEO
