TensorFlow Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used TensorFlow
Tan Pham
Last position:
DevOps Engineer in the DevOps Team at Rise-World
- Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
- Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
- Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
- Use of Scrum and Kanban methods.
- Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
- Development of new plugins and add-ons needed on current infrastructure.
- Database support.
- Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
- Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
- Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
- Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
- Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
- Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
- Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
- Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
- Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
- Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
- Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
- Automated system provisioning and deployment using CloudFormation templates.
- Configuration of IAM roles, policies and permissions to ensure secure access control.
- Patch management, backup automation and disaster recovery setup on AWS infrastructure.
- Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
- Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
- Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
- Configuration of AWS CloudWatch to monitor application performance and system events.
- Planning and execution of migration of on-premises applications to AWS cloud platforms.
- Deployment of containerized applications using Docker and Kubernetes in AWS environments.
- Deployment of internal software packages between availability zones using AWS CodeDeploy.
- Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.
Alona Liuzniak
Last position:
AI Architect
AI-powered platform for automated UX validation and designer support
- Designed and led technical implementation of an enterprise-wide AI solution for automated UX review that improved design quality and significantly reduced manual review processes in teams
- Developed an automated UX validation tool as a Figma plugin and web application that generates test cases based on internal guidelines and reliably checks current designs for consistency and standard compliance
- Implemented an interactive designer chat based on RAG that answers questions about the current design and the company's UX guidelines, and designed the deployment architecture using containerized services
- Python, Azure OpenAI, PostgreSQL, REST API, Docker, OpenShift, Helm, CI/CD, Figma MCP, LLM, RAG, Prompt Engineering, GenAI, XAI, AI Architecture, AI Strategy
Garima Chomal
Last position:
IT Program Director at Trax Retail
- Directed global digital transformation programs enabling enterprise adoption of AI-powered retail analytics solutions
- Led migration from legacy platforms to cloud-based ecosystems, improving data processing performance by over 40%
- Served as strategic technology advisor to enterprise customers, aligning technology roadmaps with business objectives
- Managed cross-functional global teams of 100+ resources across multiple regions
Umer Dilpazir
Last position:
Activation and Vocational Integration Program with Integrated Language Support at Berlitz
- Intensive language course with a focus on professional language content.
Harsh Vardhan Agrawal
Last position:
System and Process Integrator 2 at Audi AG
Spearheaded the development and deployment of a Generative AI solution tailored for the automotive industry focusing on improving customer experience through AI-driven innovations.
Conducted in-depth market research to understand unique challenges and opportunities within the automotive sector by analyzing industry trends, customer pain points, and competitive offerings to inform the product strategy.
Formulated a strategic vision for the Generative AI solution targeting personalized customer experiences, aligned product vision with the company’s long-term goals and automotive market demands.
Enhanced customer satisfaction by introducing personalized AI-driven features, achieving a 15% increase in customer engagement and loyalty.
Attended and represented Audi AG on a group-wide level in workshops for AI strategy for customer experience.
Leveraged knowledge of recurrent neural networks and transformer architecture.
Utilized GPT-3 generative AI frameworks.
Employed TensorFlow and PyTorch for machine learning.
Used Tableau from Salesforce for data analysis and visualization.
Served as solution manager for the Business Architecture team.
Collaborated with business stakeholders within Audi OEM to gather requirements for CRM strategy including marketing department, CRM heads across countries, VW group brands and CARIAD SE.
Represented Audi AG in CRM strategy workshops held in different countries.
Discussed CRM strategy with head of CRM and Data based on workshop outcomes.
Conducted business analysis on gathered market data to improve customer experience.
Planned and launched marketing campaigns such as welcome mailing, license renewal reminders, Audi Progress Circle and Black Friday campaigns.
Managed project budget.
Acted as solution manager for the ONE.CRM team at CARIAD SE on loan from Audi AG.
Collaborated with business owners of VW group brands to develop a central solution.
Represented CARIAD SE in CRM strategy workshops in Spain, France and Italy.
Discussed CRM strategy with head of CRM at CARIAD SE based on workshop outcomes.
Conducted business analysis on market and brand data to improve customer experience.
Planned and delivered campaign capabilities from template to brands such as welcome mailing for Audi AG, SEAT and SKODA.
Managed project budget together with head of CRM.
Thomas Lagemann
Last position:
Computer Vision Engineer at Dr.-Ing. Lagemann
- Freelance development engineer for image processing systems
- Development of custom image processing algorithms
- Creation of industrial image processing applications
- Training and mentoring
Discover over 15,000 top freelancers
Statistics of experts using TensorFlow
Aggregated from the professional profiles of matched freelancers.
Experience
19 years (Germany: 12 years)
Position duration
2.5 years (Germany: 2 years)
Positions per freelancer
11 (Germany: 8)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Marketing
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
67% (Germany: 81%)
Doctorate
17%
Certifications per freelancer
6 (Germany: 2)
Most common languages
German, English, Italian
Speak two or more languages
83% (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 Frankfurt 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 Frankfurt using TensorFlow
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 TensorFlow does
TensorFlow is used to build machine learning systems that learn from data and make predictions. Teams use it for image classification, text processing, forecasting, recommendation logic, and other models that need training, testing, and deployment.
Core workflow
- Data preparation and feature work
- Model design with TensorFlow and Keras
- Training, tuning, and evaluation
- Export for serving or edge use Strong specialists know how to move from notebooks to stable production code without breaking repeatability.
Ecosystem and tools
TensorFlow often sits with Keras, TensorBoard, SavedModel, TensorFlow Lite, and TensorFlow Serving. Good professionals also understand Python, NumPy, data pipelines, GPU setup, and the surrounding infrastructure needed for reliable training runs.
When companies bring in experts
Businesses look for TensorFlow expertise when an internal team needs help shipping a first model, fixing unstable training, or improving inference speed. In Frankfurt, this often fits teams working with finance, logistics, retail, or industrial data that need careful collaboration and clear documentation.
What strong professionals deliver
A strong TensorFlow specialist writes clean model code, tests data assumptions, and watches for drift, leakage, and brittle preprocessing. They can explain trade-offs between accuracy, latency, and maintainability, then adapt the system for batch scoring, online inference, or mobile deployment.
Working style
- Clear handover of data, code, and model artifacts
- Git-based work with reproducible environments
- Remote delivery or on-site sessions in Frankfurt
- Communication with product, data, and engineering teams TensorFlow work goes best when scope, inputs, and success criteria are defined early. That keeps the model useful after the first release.
Frequently asked questions
Key details about TensorFlow, drawn from the questions we get asked most.
TensorFlow is used to build machine learning systems for prediction, classification, ranking, and pattern detection. Common use cases include image analysis, language tasks, forecasting, and recommendation workflows. It is also used when a model must move into production and stay maintainable.
TensorFlow is often chosen when teams want a broader production path, especially around deployment, serving, and mobile options. PyTorch is also popular, especially in research-heavy work. The better choice depends on your team’s workflow, deployment target, and how much production tooling you need.
A strong TensorFlow specialist usually works comfortably with Python, Keras, NumPy, and data preparation. Skills in model evaluation, feature engineering, and deployment tooling matter just as much as the framework itself. For production work, knowledge of APIs, containers, and cloud infrastructure is valuable.
A TensorFlow project can start with a focused specialist if the task is clear, such as training a first model or improving an existing pipeline. More complex work, like serving models at scale or handling sensitive data, needs deeper production experience. The real question is whether the expert has shipped similar systems before.
Most TensorFlow work can be done remotely because the core tasks are code, data, and model review. On-site time in Frankfurt can help when stakeholders need workshop sessions, data access discussions, or close alignment with local teams. A hybrid setup often works well.
Ask what kind of TensorFlow models they have built, how they handle data quality, and how they validate results. Also ask how they approach deployment, monitoring, and reproducibility. A good answer should sound specific, not generic.
TensorFlow and Keras are closely linked, and many teams use Keras as the easier model-building layer. It helps with fast prototyping while still supporting serious training workflows. If your project needs speed and clarity, asking for Keras experience is often smart.
A strong TensorFlow specialist can explain why a model behaves the way it does and what was done to improve it. Look for clear experiments, sensible evaluation, and careful handling of data leakage and overfitting. Good experts also document assumptions so others can maintain the work later.
The average hourly rate of freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects is 100 €, which corresponds to a daily rate of about 799 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects, 100% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects are German (83%), English (83%), and Italian (17%).
The most common industries among freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects are Information Technology (100%), Automotive (50%), and Banking and Finance (50%).
The most common business areas among freelancers in Frankfurt, Germany who have used TensorFlow in their recent projects are Information Technology (100%), Product Development (83%), and Business Intelligence (67%).
Main locations of FRATCH Experts, who have recently used TensorFlow
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 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
