Machine Learning Experts in Hamburg
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Meet FRATCH Experts in Hamburg, who have recently used Machine Learning
Daniel Sedlack
Last position:
Senior Software Engineer at energielenker solutions GmbH
- Designed and implemented a Python-based ETL pipeline with the Dagster framework to transform raw energy data from heterogeneous sources using InfluxDB and visualizations in Grafana
- Defined time-based and dependency-based jobs
- Deployed to managed Kubernetes clusters using Helm
- Integrated InfluxDB Cloud
- Prepared data for use in Grafana, including cleaning, normalization, and time-based resampling in Python
- Developed dashboards and visualizations in Grafana
- Developed unit tests with mocking using pytest
- Set up a CI/CD pipeline in GitLab
Technologies: Python, Dagster, InfluxDB, Grafana, pandas, pytest, REST, CI/CD, GitLab, Container, Kubernetes, Helm, Docker, Cloud
Sanchit Bhavsar
Last position:
Freelancer at S2S Dynamics UG
- Implementing cross-industry applications with LLMs
- Developing cloud infrastructure for clients
- Implemented end-to-end data pipeline to deploy models in real time
- Managed overall IT system administration and desktop support
Rutger Boels
Last position:
Partner & Managing Director at AI.IMPACT
- Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
- End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
- Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
- Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
- Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
- Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
- Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles
Anastasiia Komarenko
Last position:
Senior Test Automation Engineer at E.ON
- Reviewing functional and technical requirements from a testing perspective
- Creating test cases and automated tests to validate requirements
- Performing manual and automated functional, end-to-end, and regression tests
- Documenting test results and tracking defects
- Using models like GPT-4, BERT, and Hugging Face Transformers for automated test case generation, analysis of test results, and improving test coverage, including bias checks and security reviews
- Techs: MS Office, Jira, Zephyr, Confluence, Tosca, stakeholder communication, Agile, Kanban, Scrum, OpenAI API, Hugging Face, PyTorch, LangChain.
Cornelius Höfig
Last position:
Solution Architect at STIHL
- Remodeling of the system architecture for an Azure-based platform aimed at rapid development of new functionalities
- Modeling of a staging concept for the fulfillment of diverse customer and QA needs
- Creation of requirements for, and oversight of, a proof-of-concept supplier project for a Flutter app with highly advanced BLE functionalities
- Comparison of multiple observability platforms for feasibility and requirements fit within the project environment
- Creation of a mobile app architecture based on domain-driven architecture
- Position of technical advisor and accountable solution architect for two development teams
- Execution of architecture reviews and alignment of changes with architectural expectations
- Skills & Technologies: Microsoft Azure , App Services, NodeJS Mono-repository, microservice architecture, domain driven design, self contained systems, requirements engineering, CI/CD, DevOps, API design, solution architecture
Heena Patel
Last position:
Retirement Spend & Tax Optimizer Agentic AI App (Vibe Coding) at Personal Project
Self-directed exploration of agentic AI development methods, taken from idea to a working, publicly usable application
- Built an interactive planning tool for modelling retirement withdrawals and tax strategy using an agentic AI (vibe coding) development approach – demonstrating self-directed investigation of new AI-assisted development methods
- Delivered live, tax-aware spending projections and adjustable user inputs; shipped as a free, install-free browser application built in Python, with attention to usability for non-technical users
Jenny Lam
Last position:
Product Manager – Data & Sustainability at shipzero GmbH
Designed and implemented an initial product management framework
Created a process for prioritizing the product roadmap with internal stakeholders, considering business impact, resources, and technical feasibility
Led the migration to a product discovery tool to improve transparency and cross-team collaboration
Served as a liaison between tech and business teams
Managed data-driven sustainability projects for the largest key account, including implementing regulatory reporting (ISO 14083) on greenhouse gas emissions
Delivered complete data integration across 20+ source systems, coordinating onboarding and translating business requirements into technical specs for the development team
Enhanced the client's emission tracking and reporting accuracy through data quality analyses and identifying optimization opportunities
Marc Matt
Last position:
Freelance Data Specialist at BrightlySoftware – A Siemens Company
- Migration of customer data from a private cloud to AWS
- Optimizing data transformation jobs and migration from Talend to AWS Glue
- Automation of all migration steps
- Used technologies: AWS, Python, Lambda, CloudFormation, SQLServer, AWS Stepfunctions, Glue, PySpark
Dominik Piecuch
Last position:
Head of IT at Aarsleff Spezialtiefbau GmbH
- Disciplinary and professional leadership of the IT and service team
- Definition and documentation of the Current Mode of Operation (CMO) in Confluence: application landscape, infrastructure, networks, backup & storage
- Development of the Future Mode of Operation (FMO) including process analysis & stakeholder interviews with all departments using BPMN and flowcharts
- Optimization of license management: reduction of ongoing software costs by approx. 17% p.a.
- Introduction and establishment of Jira as the central tool for project and service management
- Introduction and rollout of the HR software MindKey to digitize HR processes
- Introduction of a VoIP solution with Microsoft Teams incl. PSTN connection to replace classic telephony
- Introduction of the production and planning software OptiControl to digitize operational processes
- Rollout of Intune as a Mobile Device Management solution for Windows, iOS and Android
- Build-up of Power BI dashboards for machine park monitoring and financial reporting
- Planning and execution of the IT consolidation of two locations for 170 users
- Introduction of automated penetration testing with Pentera
- Coaching and mentoring the team in agile methods & project management
- Operational support in day-to-day business: administration, incident & change management
- Management of external service providers and assurance of the quality of outsourced IT services
- Responsibility for the IT budget incl. planning and controlling
- Direct reporting line to management with regular management reports on IT KPIs, budget and project status
Florian Wede
Last position:
Software Engineer at micimo GmbH
- Developing a professional scheduler for organizations with specific detailed requirements
- Evaluating different existing software solutions
- Creating a list of technical requirements
- Implementing these requirements
- Selected technologies: WebDAV, CalDAV, Rust, Baikal, OAuth, Keycloak
Marcus Brandt
Last position:
Managing Director at Petermann Brandt GmbH
- Development and implementation of custom IT solutions for key customers.
- More than 15 years of experience in IT and project management, disciplinary leadership of up to 80 employees.
Andreas Dietrich
Last position:
Interim Chief Technology & Product Officer at Babbel GmbH
- Restructuring for product-led growth in the field of digital user-centric tech product development language learning experiences
- Scaling empowered tech product teams
- Anti-fragile software engineering
Tungi Dang
Last position:
Technical PMO | Delivery Master | LLM-Expert at Stealth - NDA
- Owning RAG, LLM-System, ML-ops-Pipelines for various startups in Insurance, Banking, Energy (KRITIS)
Paolo Baldriga
Last position:
Head of Demand Analytics at Zalando
- Leading Demand Analytics to turn data, AI and forecasting insights into strategic decisions across markets.
- Driving AI-powered demand planning and personalization to improve customer engagement, retention and revenue.
- Partnering with Product, Commercial, Marketing and Finance to align analytics with growth targets.
- Building and mentoring international analytics teams to scale impact, speed and decision quality.
Andreas Schmückert
Last position:
Solution Architect, Business Analyst, Consultant, Full-Stack Lead-Developer at 50Hertz Transmission GmbH
- Solution for micro-service and frontend solution for the electric grid
- Leading of development teams
- Technologies: React-Native, TypeScript, Kotlin, AWS, Infrastructure As Code, Serverless Architecture, React, NoSQL, GraphQL, Angular, Playwright, Python, ML(Ops), Kubernetes, Docker
Discover over 15,000 top freelancers
Statistics of experts using Machine Learning
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
2.3 years (Germany: 2.8 years)
Positions per freelancer
7 (Germany: 8)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Professional Services, Education
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
71% (Germany: 77%)
Doctorate
23% (Germany: 19%)
Certifications per freelancer
3 (Germany: 2)
Most common languages
English, German, 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 Hamburg 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 Hamburg 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 ML covers
Machine Learning turns data into predictions, classifications, rankings, and recommendations. It is used for demand forecasting, anomaly detection, search relevance, fraud signals, and customer personalization. In practice, teams often shorten it to ML.
Common stacks
- Data prep in Python, pandas, and SQL
- Model work with scikit-learn, XGBoost, TensorFlow, or PyTorch
- Experiment tracking, validation, and feature engineering
- Deployment into APIs, batch jobs, or event-driven services
Where it fits
Strong Machine Learning work connects product goals with data reality. Experts define target variables, choose evaluation metrics, test leakage risks, and tune models so they hold up in real use. They also make sure the solution fits the existing stack and release process.
When to bring help
Companies bring in freelance specialists when a model must move from proof of concept to production, when an existing ML system drifts, or when internal teams need extra hands for a specific use case. In Hamburg, that often comes up in logistics, commerce, media, and industrial settings.
What strong experts do
- Turn business questions into measurable ML tasks
- Work with structured, text, image, or time-series data
- Explain model trade-offs in plain language
- Build for monitoring, retraining, and maintainability
Delivery and collaboration
Good ML professionals deliver more than a notebook. They leave behind reproducible training code, clear evaluation logic, and deployment-ready artefacts. Remote work is common, but on-site sessions in Hamburg help when data access, stakeholder reviews, or domain discovery need close coordination.
Frequently asked questions
Everything clients usually want to know about Machine Learning, in one place.
Machine Learning usually means building systems that learn patterns from data and produce predictions, scores, or recommendations. Companies use it for forecasting, classification, ranking, anomaly detection, and personalization. The work is only useful if the model can be measured and maintained in real operations.
Machine Learning learns behavior from examples, while rules-based automation follows instructions written by people. That makes ML better for tasks where patterns are complex or change over time, such as spam detection or demand prediction. Rules can still help around the model, especially for guardrails and edge cases.
Machine Learning is the broader field, and many projects work well with simpler methods such as linear models, random forests, or gradient boosting. Deep learning is usually chosen for large-scale text, image, audio, or sequence problems. A good specialist picks the simplest method that meets the goal.
A strong Machine Learning specialist usually knows Python, SQL, data preparation, feature engineering, validation, and deployment basics. Familiarity with scikit-learn, TensorFlow, PyTorch, or XGBoost is common, along with clean experiment tracking. Product thinking matters too, because the model must solve a real business problem.
For Machine Learning, you do not need a finished data science brief, but you do need a clear business goal and access to relevant data. The best starting point is a problem statement, the available data sources, and the way success will be judged. A good expert can help shape the rest.
Yes, Machine Learning work is often well suited to remote collaboration because most tasks happen in code, data, and review sessions. Still, on-site time can help when data access is sensitive or when the team needs close domain input. For Hamburg-based teams, a hybrid setup is common when local meetings add value.
ML is often compared with deterministic software, statistical forecasting, and business intelligence rules. The right choice depends on whether the problem needs learned patterns, explainable thresholds, or reporting only. A solid specialist helps decide if ML is justified before any model work starts.
Machine Learning quality is shown by more than a good training score. Look for clear target definition, proper validation, low leakage risk, stable performance on unseen data, and a plan for monitoring after launch. Good documentation and reproducible code are also strong signs.
The average hourly rate of freelancers in Hamburg, Germany who have used Machine Learning in their recent projects is 110 €, which corresponds to a daily rate of about 883 € based on an 8-hour working day.
Of the freelancers in Hamburg, Germany who have used Machine Learning in their recent projects, 100% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 23% hold a doctorate.
On average, freelancers in Hamburg, Germany who have used Machine Learning in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Hamburg, Germany who have used Machine Learning in their recent projects are English (100%), German (97%), and French (21%).
The most common industries among freelancers in Hamburg, Germany who have used Machine Learning in their recent projects are Information Technology (82%), Professional Services (45%), and Education (42%).
The most common business areas among freelancers in Hamburg, Germany who have used Machine Learning in their recent projects are Information Technology (91%), Product Development (79%), 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.
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Munich 
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Stuttgart 
Dusseldorf 
Dortmund 
Essen 
Bremen 
Dresden 
Hanover 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
