Find the perfect AI Engineer in Frankfurt in minutes from over 15,000 CVs with the power of AI.
Access freelance machine learning experts, NLP specialists, and computer vision developers in Frankfurt. Get matched with vetted, available professionals ready to integrate LLMs, build predictive models, or optimize your AI pipelines.
About the role
Deep Tech Expertise for Intelligent Systems
An AI engineer bridges the gap between theoretical machine learning models and practical software solutions. These specialists design, build, and deploy production-ready artificial intelligence systems that automate complex business processes, improve decision-making, and analyze unstructured data. They translate complex mathematical concepts into clean, maintainable code that scales efficiently within corporate environments.
Key Technologies and Machine Learning Frameworks
- Deep learning frameworks such as PyTorch, TensorFlow, and Keras
- Large language model integration, fine-tuning, and prompt engineering
- Natural language processing libraries like Hugging Face, spaCy, and NLTK
- Cloud AI services across AWS, Microsoft Azure, and Google Cloud Platform
- MLOps tools for pipeline automation including Kubeflow, MLflow, and DVC
- Solid software engineering in Python, C++, and containerization with Docker
Strategic AI Integration in Frankfurt
The Frankfurt business landscape, dominated by financial institutions, fintech startups, and logistics hubs, increasingly demands specialized AI capabilities. Freelance experts help local organizations navigate strict regulatory frameworks while deploying predictive models, automated risk assessment tools, and intelligent document processing systems. Working with freelance professionals allows local teams to rapidly inject cutting-edge tech expertise into legacy environments without long-term overhead.
Project Deliverables and Milestones
- Functional proof-of-concept models validated against business metrics
- Production-ready API endpoints for seamless model integration
- Automated data preprocessing and model training pipelines
- Comprehensive documentation of architecture, algorithms, and training datasets
- Optimized model weights and configurations for low-latency inference
- Security and compliance audits for data processing pipelines
Meet FRATCH AI Engineers
Ali Aminian
Enterprise Software Architect | Cloud, Integration & AI Platforms
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Malte Lohrberg
Product Owner, Product Developer, AI Manager & Organizational Consultant
Last position:
Product Owner, Change Management Coach and Organizational Consultant & Founder and Product Architect at Freelance + Resilience Bakery
The combined experience from recent project years shows that two hearts beat in my chest: on the one hand, working in and for organizations to develop new, innovative products, ideally as part of a digitization strategy or business development – and the closely related change and transformation process expertise as part of holistic organizational consulting. For this, I have established the Change Bakery and Product Validators offerings.
On the other hand, my heart and mind are fired up to find my own products, evaluate markets and potentials, and test ideas. Currently, I am proactively and part-time, in addition to ongoing projects, working on a product idea in the mental health area and have founded Therapymate.
Benedikt Ruske
Experienced Data & Business Analyst with a focus on Power BI and Business Intelligence
Last position:
Power BI developer at Mechanical Engineering (SME 500 emp.)
- KPI dashboards for inventory and goods received quality control & testing ETL, dataset, dataflows and report development, complex DAX solutions
Data sources: Dataverse, RDB, Excel
Tools: ETL, data modeling, data flows, Power Query, M, Power BI, complex DAX
- Capacity: 25%
Kabir Khaleque
AI Engineer / Banking IT Specialist
Last position:
AI Engineer / Banking IT Specialist at Hamburg Commercial Bank (HCOB) & Real Estate Firm
- Developed a retrieval-augmented generation (RAG) application using LangChain and LangGraph for corporate document parsing, delivered as an installable Electron desktop application with local AI models via Ollama.
- Currently providing ongoing AI feature support for the Loan Pricing Tool at Hamburg Commercial Bank, with a commitment of three days per month.
- Architected Kubernetes-native solutions, including Helm chart configuration and Azure DevOps pipeline integration.
Eduard Van Kleef
Workshop Leader 'Introduction to AI Development Tools'
Last position:
Workshop Leader 'Introduction to AI Development Tools' at Software company in Wiesbaden
- Presentation introducing generic AI and large language models
- Explanation of legal frameworks (EU AI Act, US CLOUD Act, GDPR)
- Systematic review of AI tools along the SDLC and holistic systems
- Comparison of on-prem LLMs vs. cloud-based, as well as change management and works council
- Facilitated the discussion and derived next steps for introducing AI development tools
Michael Yaco
Senior Consultant, Senior DevOps Engineer
Last position:
Senior Consultant, Senior DevOps Engineer at DB Regio AG
- Supported implementation and operation of a portal used online and offline in customer-facing vehicles
- Automated processes by introducing CI/CD pipelines
- Provided enablement and methodological guidance for adopting software engineering best practices
- System environment: NestJS, Node.js, npm, AWS, Docker, Docker Swarm, GitLab CI, WhiteSource, PostgreSQL, Prometheus, Grafana, OpenSearch, REST API
Anton Rösler
AI-Engineer
Last position:
AI-Engineer at Publicly traded company, industrial safety technology
- Designed and implemented the agent-based AI architecture for a company-wide platform to securely deploy LLM-based agents
- Designed and implemented end-to-end RAG pipelines from multiple sources: document preprocessing, chunking strategies for different document types, embeddings, retrieval with re-ranking, and robust prompt orchestration
- Developed a modular context engineering framework with skill architecture, context isolation, and dynamic resource management; human-in-the-loop control for enterprise tool integrations
- Built the CI/CD pipeline, testing strategy, tracing on the software side as well as automated LLM and agent evaluations, red team testing and tracing, and handed over to a reproducible production environment (ISO27001 and SOC2 compliant)
Discover over 15,000 top freelancers
AI Engineers statistics
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
2.5 years
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Banking and Finance, Manufacturing
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100%
Master's degree or higher
33%
Certifications per freelancer
4
Most common languages
German, English, Arabic
Speak two or more languages
100%
Daily Rate Distribution
The chart shows how the daily rates of freelancers in this role 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. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Average rates for AI Engineers & Seniority distribution
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.
Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Frequently Asked Questions
Do you have questions? Here you can find further information about FRATCH
An AI engineer designs, builds, and deploys machine learning models and neural networks into production environments. They handle everything from data preprocessing and pipeline creation to model training, fine-tuning, and API integration, ensuring the system runs efficiently at scale.
While a data scientist focuses on analyzing data, finding insights, and building prototypes, an AI engineer is responsible for writing production-ready code, deploying models, and integrating those models into software systems. Their focus is on software engineering, scalability, and system architecture.
Many financial institutions and logistics firms in Frankfurt prefer a hybrid work model, especially during the initial architecture phase or during security-sensitive deployment stages. However, the majority of development and coding tasks are successfully completed via remote collaboration.
A professional AI developer must have deep expertise in Python, as well as libraries such as PyTorch, TensorFlow, and Hugging Face. Knowledge of cloud platforms like AWS or Azure, combined with experience in containerization, is also essential for modern deployment.
Yes, an experienced AI programmer working with German clients ensures that all models comply with GDPR and local data privacy laws. This includes implementing secure data handling practices, anonymization techniques, and utilizing private or local hosting solutions for language models.
Hiring a freelance AI specialist allows companies to scale up quickly for complex migration or implementation projects without long-term commitment. It gives you immediate access to highly specialized skills for specific phases, such as setting up an MLOps pipeline or deploying a custom model.
The banking, fintech, insurance, and logistics sectors in the Frankfurt Rhine-Main region heavily rely on external machine learning engineers to automate risk assessment, fraud detection, and document processing. These industries benefit from rapid implementation cycles that keep them competitive.
You can evaluate an artificial intelligence engineer by reviewing their past production deployments, GitHub repositories, and their ability to explain complex algorithm choices. Strong candidates demonstrate a solid understanding of both software engineering principles and machine learning theory.
The average hourly rate for AI Engineers in Frankfurt is 110 €, which corresponds to a daily rate of about 879 € based on an 8-hour working day.
Of the freelancers working as AI Engineers in Frankfurt, 100% hold at least a Bachelor's degree and 33% hold at least a Master's degree.
On average, freelancers working as AI Engineers in Frankfurt have 20 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers working as AI Engineers in Frankfurt are German (100%), English (100%), and Arabic (14%).
The most common industries among freelancers working as AI Engineers in Frankfurt are Information Technology (71%), Banking and Finance (57%), and Manufacturing (57%).
The most common business areas among freelancers working as AI Engineers in Frankfurt are Information Technology (100%), Product Development (100%), and Quality Assurance (86%).
FRATCH AI Engineers main locations
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
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
