
Large Language Model Experts in Cologne
matched in minutes from over 15,000 CVsHire experts who design retrieval-augmented applications, adapt language models with fine-tuning and evaluation, and connect them to secure business workflows. FRATCH matches you quickly and precisely with vetted, available freelancers for your project.
Meet FRATCH Experts in Cologne, who have recently used Large Language Model
Jens R.
Last position:
Platform Architect & Senior Developer at Direct client, industrial measurement technology, medium-sized company
- Technical leadership across hardware, firmware, and software teams; scope: hardware/firmware team (4 people) and leadership group (5 people)
- Consolidated and documented a product family that had grown over more than 15 years and aligned it with CRA compliance — from the bare-metal I/O module to the cloud interface.
- Provided the most important customer product with the essential requirements and architecture documentation within two months — for a firmware landscape that had grown over more than 15 years. It now supports the customer’s modernization strategy.
- Established a monthly reporting line to the supervisory board and executive board within three months: nine meetings since 12/2025. The report itself is versioned and built from the CI pipeline; it is based on automatically collected activity and release data instead of assessments.
- Built a container-based CI/CD infrastructure from scratch: cross-compilation, host tests, and documentation builds in one continuous pipeline.
- Introduced declarative QA gates for DevOps and development artifacts — from the start using lefthook instead of pre-commit, executed in a dedicated container image.
Technologies used: arc42, req42, tpo42, docToolchain, PlantUML, ArchiMate, C4 model, ADR, C, C++ (GTest), CMake, Bare Metal (ARM Cortex-M3/M7), OCI containers, Jenkins, lefthook, Prometheus, Grafana, SBOM, CRA, OPC, SCADA, PLC integration, IPv6 migration, Zero Trust, Sociocracy 3.0, Cynefin
Burhan D.
Last position:
Enterprise Architect & Solution Architect at DB Netz AG
With project PRIZMA, DB will modernize its infrastructure on the one hand, and develop a fail-safe IT landscape on the other hand, which can be restored quickly and securely in case of a disaster.
- Capture current architectures of existing systems as well as methodical consulting and development of target architectures
- Deepen and maintain the building plan / target IT landscape
- Implement technical architecture concepts & architecture descriptions
- Implement migration concepts for updating and further developing the platform and information systems
- Assess submitted improvement suggestions as part of the project
- Capability management: identify capability gaps, develop target visions, and support transformation planning within the enterprise architecture.
- Create a compatibility matrix of the components in use and compare dependencies of specific versions
- Create an IT concept for extending the platform with the following topics: hardware and software requirements, security, licensing, high availability, load balancing, backup & recovery, update strategy, monitoring integration, etc.
- Coordinate with business architects as well as technical architects from the cross-functional architecture area of the PRISMA program for the topics (backup, Active Directory, monitoring, Citrix, and business applications ...)
- Status meetings and alignment of project planning with the Release Train Engineer / Project Manager
- Advise the Release Train Engineer / Project Manager in identifying project risks
- Advise the System Architect Engineers in steering the implementation of the concept
- Implement the IT concept
- Document the infrastructure
Label: MS Project, LINUX, Windows, ORACLE, Java, REST, SharePoint, Microsoft Exchange, UML, Enterprise Architect, BPMN, AZURE, AWS, V-MODEL, Micro Service, VisualStudio, SAP S/4HANA, SCRUM(SAFE), ESB (TIBCO), Python, Innovator, LeanIX (TOGAF), Ansible, Ansible Tower, Ansible Automation, ROBOT, SpringBoot
Piet A.
Last position:
Founder at RubberMetrics.com
- Self-hosted table tennis equipment platform.
- Development of a custom “Racket Builder” that uses a co-evolutionary genetic algorithm to identify, evaluate, and recommend the optimal combinations of racket blades and rubbers based on physics heuristics and player data within a search space of over 4 billion combinations.
- Development of a custom fully automated web crawler to capture equipment specifications, integrating an automated pipeline for image normalization as well as data harmonization via DeepSeek.
- Cloudflare Edge Workers written in Rust to perform low-latency data searches and offload computationally intensive simulations from the main server.
- High performance and accessibility standards across a large Nuxt 4 codebase achieving 95–100/100/100 Lighthouse scores.
Patrick D.
Last position:
Fullstack Developer
- SPA for automated communication of medical findings with role-based access (Sanctum)
- Server-side LLM integration (OpenRouter) with structured processing
- Automated sending via SMS/voice call (Twilio, ElevenLabs) with queue + status retry
- Full test coverage with 80+ documented test cases
Technologies: PHP, Laravel, LLM API (OpenRouter), Twilio, ElevenLabs, Laravel Sanctum, PHPUnit, Playwright, Docker, REST
Hassan A.
Last position:
DevOps & Observability Consultant at ALDI South (Albrecht's Discount)
- Supporting the DevOps team in Terraform-managed, multi-region AWS infrastructure to achieve environment parity.
- Developed end-to-end CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy, automating the build and deployment.
- Maintained pre- and post-deployment scripts to automate critical tasks such as database schema migrations and environment sanity checks.
- Implemented CI/CD flow specifically for hotfixes via separate Git branches, managing back-merge activities from feature branches to release branches to ensure code integrity through automated conflict resolution.
- Deployed a dedicated, lightweight sanity check application hosted cost-effectively on Azure Container Apps to run automated health and basic functional checks as a post-deployment activity triggered via pipeline.
- Investigated production incidents through code changes and AWS CloudWatch logs.
- Coordinated integration of Dynatrace APM and its APIs for monitoring purposes.
- Full stack QA strategist for a high-traffic e-commerce platform built on a layered architecture for the back-end testing of core platform services, especially the order management system in Zed and Glue layers.
- Managed automation activities, testing process, and refactoring practices.
- Responsible for framework migrations, setup, and training for new automation frameworks.
- Promoted a shift-left approach within the QA team and created the test concept.
- Participated in meetings with IT managers, business owners, product owners, and team members.
- Designed and implemented contract testing to validate API schema compatibility between the order management system and the Zed and Glue layers, reducing production-relevant breaking changes by approximately 3%.
- Led the migration to a multi-environment framework that enabled test execution across 4 country configurations from a single codebase.
- Integrated automated unit and functional tests directly into the GitLab CI/CD pipeline, reducing pipeline runtime by 32%.
- Coached and trained 5 QA engineers across Germany and Hungary in test automation, framework architecture, and best practices.
- Architected a layered backend test automation framework separating business logic, API request builders, and the database layer.
- Piloted AI-assisted testing with Playwright Agents, the Playwright MCP Server, and GitHub Copilot for automated test generation, execution, and self-healing Playwright scripts.
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Marc R.
Last position:
CTO Coach at zvoove Switzerland
- Coaching the CTO on translating the product strategy into technical strategy and AI transformation of the R&D organization; acting as an independent sparring partner on strategic and technical topics
Hans R.
Last position:
Founder at N+One
Building an AI-native coaching platform for cyclists: a conversational Dynamic Coach that turns training and recovery data into the next session decision, available daily instead of a static calendar.
Designed and shipped a full-stack, chat-first coaching experience on Next.js and the Vercel Edge Network, with agentic workflows that adapt plans in real time to readiness, load, and life constraints.
Built integrations with Garmin, Strava, Whoop, and intervals.icu so sleep, HRV, and ride data feed coaching recommendations without manual data entry.
Product thesis: make high-quality coaching principles accessible at scale by combining adaptive training logic with plain-language conversation, not another metrics dashboard.
Alexander K.
Last position:
Software Tester at Buhl Tax Service GmbH
- AI-assisted creation of test cases and test data
- Creation of test cases based on requirements
- Execution of manual tests
- Defect documentation, retesting and tracking
Technologies & Tools: SCRUM, Jira, Confluence, Zephyr Scale
Fahad R.
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
Simon K.
Last position:
Senior Digitalization Consultant at Ginkgo Management Consulting
- Consulting and implementation of digitalization projects nationally and internationally for start-ups, SMEs and large corporations
- Focus areas: design systems, RAG & automations
- Tools and technologies: Claude, GPT, Gemini
Thomas P.
Last position:
GenAI Customer Experience Lead at Samsung Electronics
- Leading initiatives to improve the retrieval and representation of Samsung support content in AI-generated answers, including authoring editorial standards and educating stakeholders on representation risk.
- Developing initial frameworks to measure and evaluate brand representation in AI-generated answers (LLMs, Google AI environments), including prompt baselines and scoring models.
Jeanne Y.
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
Marc S.
Last position:
Fullstack Developer at PLANT-MY-TREE
PLANT-MY-TREE®-per-order
The application enables Shopify merchants to automatically place tree-planting orders for every incoming order. By integrating ecological contributions directly into the purchase process, the manual effort for tracking and billing reforestation initiatives is eliminated. The system increases transparency for end customers through real-time visualizations of the ecological impact directly in the storefront. The architecture is based on a modular monolith with Spring Boot in the backend and an integrated React app inside the Shopify admin area. The solution uses webhooks to capture order data in an event-driven way and integrates the weclapp ERP system for automated monthly invoicing. An app proxy mechanism provides dynamic statistics such as CO2 compensation and planted trees without any performance loss for the merchant shop.
Tasks:
- Design of the modular software architecture based on Spring Modulith to ensure high maintainability
- Development of the event-driven business logic for evaluating Shopify orders via webhooks
- Implementation of automated invoicing by connecting the weclapp REST API
- Building the frontend using React Router and Shopify App Bridge for native integration
- Design of the database model and implementation of the persistence layer with JPA/Hibernate and Prisma
- Integration of internationalization processes for global use in the frontend and email communication
- Automation of deployment processes using Docker and GitLab CI/CD
Project skills: Java 25, Spring Boot, Spring Security, Spring Modulith, Hibernate, JPA, REST API, PostgreSQL, Maven, Liquibase, React, TypeScript, React Router, Vite, Node.js, Prisma, Zod, Docker, Docker Compose, GitLab CI/CD, Shopify CLI, Shopify App Bridge, Polaris, weclapp, i18next, Lombok, Vitest
Allal K.
Last position:
Java Senior Full Stack Developer at Insurance ÖRAG
- Further development of a policy administration system (contract/claims) for the legal expenses insurer ÖRAG.
- My role: Senior Software Developer.
- The team consists of 12 developers.
- Technologies used: Java 8/21, Java EE, Quarkus, WebLogic, JPA, RabbitMQ, JTA, CI, CD, Jenkins, DB2, Maven, Jenkins, GIT (bitbucket) later GitLab, Junit, Elasticsearch, Mockito, Jira, SonarQube, Scrum, React, Workflow
- Migration and modernization of legacy systems: rewrote C and C++ code in Java to improve maintainability, scalability, and performance. Refactored Python into Java, including optimization and integration into modern architectures.
- Study on the use of AI (Codex) for implementing a Java feature. The goal is to compare the time spent and productivity of AI-supported development with a classic implementation by a developer. The results should show how strongly the use of AI affects development time and efficiency.
- Development of the following tariff calculators for the years 2024/2026: private, companies, doctors, farmers, owner-occupied G + H, landlords, traffic, club, top managers, sales representatives, special criminal law, savings bank, municipal, BayGT, doctors, Dehoga
Discover over 15,000 top freelancers
Statistics of experts using Large Language Model
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 15 years)

Position duration
1.9 years (Germany: 2.9 years)

Positions per freelancer
11 (Germany: 10)

Top business areas
Information Technology, Product Development, Project Management

Top industries
Information Technology, Professional Services, Education

Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
86% (Germany: 95%)
Master's degree or higher
57% (Germany: 70%)
Doctorate
10% (Germany: 13%)

Certifications per freelancer
3

Most common languages
German, English, French

Speak two or more languages
100% (Germany: 97%)
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Cologne are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Cologne using Large Language Model
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Large Language Model 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 (93%)
- Professional Services (59%)
- Education (52%)
- Retail (52%)
- Automotive (41%)
- Banking and Finance (33%)
- Healthcare (33%)
- Transportation (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Large Language Models do
Large Language Models, often called LLMs, process and generate human language. They support conversational assistants, document search, summarisation, classification, translation and content workflows. An LLM can work with text, code and, when supported, images or other inputs.
Products and use cases
Companies use LLMs to turn unstructured information into useful actions and answers.
- Customer and employee assistants grounded in approved content
- Retrieval-augmented search across contracts, manuals and knowledge bases
- Document extraction, classification and summarisation
- Software copilots, content tools and workflow automation
Ecosystem and tooling
LLM work connects model providers such as OpenAI, Anthropic, Google and open-weight models from Meta or Mistral with application code. Specialists work with Python, TypeScript, APIs, vector databases, embedding models and orchestration tools such as LangChain or LlamaIndex. They also handle cloud deployment, observability and access controls.
When companies need specialists
Freelance expertise is useful when a proof of concept must become a reliable product, when model output is inconsistent, or when sensitive data needs careful handling. In Cologne, teams across media, logistics, manufacturing, business services and research may need support integrating language models into existing systems. Remote collaboration works well when interfaces, data access and review processes are clearly defined.
What strong professionals deliver
Strong specialists start with a measurable use case rather than choosing a model first. They compare prompts, models and retrieval strategies, create representative test sets and document trade-offs. They design fallbacks for uncertain answers, protect personal and confidential data, control usage costs and make model behaviour visible in production.
Skills to assess before hiring
Look for practical experience across the full LLM application lifecycle.
- Prompt design, structured output and tool calling
- Retrieval pipelines, chunking, embeddings and reranking
- Fine-tuning, evaluation and red-team testing
- Data protection, security, monitoring and deployment
- Clear communication with product, legal and domain teams
For Cologne-based collaboration, confirm whether on-site workshops are needed and which language the product and documentation require. The best professional can explain limitations plainly and transfer knowledge to the internal team.
Frequently asked questions
Curious about Large Language Model? Here are the answers that come up again and again.
Large Language Models are used for assistants, semantic search, document processing, summarisation, translation and software support. They can also call business tools when surrounded by suitable application logic, permissions and validation.
An LLM can interpret varied language and generate responses instead of relying only on fixed rules or scripted paths. A dependable application still needs retrieval, guardrails, testing and human escalation where an answer could cause harm.
A strong Large Language Model specialist understands application development, APIs, data pipelines, vector search and cloud operations. Knowledge of information security, data protection, user research and domain workflows is equally valuable.
A Large Language Model freelancer should have experience taking a use case from discovery through evaluation and production. Ask for examples showing how they handled hallucinations, changing model behaviour, sensitive data, latency and operational monitoring.
LLMs are well suited to remote delivery when specialists can access representative data safely and communicate with product and technical teams. On-site sessions in Cologne can help with process discovery, stakeholder workshops or training, but they are not required for every project.
Large Language Models from hosted providers can offer fast access to strong capabilities and managed operations. Open-weight models may provide more control over deployment, customisation and data location, so the choice should reflect security, quality, infrastructure and maintenance requirements.
Ask how the LLM specialist defines success, builds evaluation data and measures factuality, relevance, safety and user acceptance. Good professionals show their reasoning, document limits and design tests that reflect real conversations rather than relying on impressive demonstrations.
A Large Language Model project does not automatically need fine-tuning. Prompt design, retrieval, structured outputs and tool integration often solve the initial problem; fine-tuning becomes relevant when consistent style, specialised behaviour or task performance cannot be achieved through those methods.
The average hourly rate of freelancers in Cologne, Germany who have used Large Language Model in their recent projects is 100 €, which corresponds to a daily rate of about 797 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Large Language Model in their recent projects, 86% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 10% hold a doctorate.
On average, freelancers in Cologne, Germany who have used Large Language Model in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Cologne, Germany who have used Large Language Model in their recent projects are German (100%), English (100%), and French (19%).
The most common industries among freelancers in Cologne, Germany who have used Large Language Model in their recent projects are Information Technology (93%), Professional Services (59%), and Education (52%).
The most common business areas among freelancers in Cologne, Germany who have used Large Language Model in their recent projects are Information Technology (100%), Product Development (81%), and Project Management (59%).
Main locations of FRATCH Experts, who have recently used Large Language Model
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.
Request a free demo
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