Keras Experts in Munich
matched in minutes by powerful AIHire experts who design, train and deploy deep learning models with Keras, TensorFlow and Python. Work with vetted, available freelancers who fit your technical needs and can contribute quickly to computer vision, natural language processing and predictive analytics projects.
Meet FRATCH Experts in Munich, who have recently used Keras
Michael N.
Last position:
Senior AI Engineer | Forward Deployed Engineer at Tiefbau
- Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
- Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
- Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.
Mirza K.
Last position:
Agentic Automation and a RAG system
- This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.
Used: Python, RAG, LangGraph, LangChain, deepeval, MCP
Philipp G.
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Narges D.
Last position:
Research Assistant at Hochschule München
Introduced an integrated approach for structural damage detection across concrete, steel, and glass using advanced technologies such as LiDAR and thermal imaging. Highlighted cross-material interactions to enhance diagnostics and enable predictive maintenance.
Developed an NLP-based medical note simplifier that transforms complex clinical instructions into plain, child-level English. Applied prompt engineering with Flan-T5 transformer models to extract patient-relevant actions and rephrase them into clear to-do items. Built dual Flask and Tornado backends with a printable web interface.
Tobias N.
Last position:
Enterprise & Solutions Architect
- Building an independent enterprise IT setup — cloud strategy, network, AWS landing zone, security requirements, contract negotiations.
- Migration of all applications; avoiding high contractual penalties for the client.
- Onboarding and coordination o...
Stephan B.
Last position:
Freelance Data Scientist at Baier Data & AI Consulting
Christian S.
Last position:
Data-Scientist/AI Engineer at The Marcom Engine GmbH & Co. KG
- Concept creation and implementing AI Agents in AWS Cloud
- Continuously alignment with stakeholders
- Collaborate with DevOps
- Technologies: Git, CI/CD (GitHub Actions), Python/ML, Streamlit, Deno/typescript, AWS SAM, AWS Bedrock, AWS Lambda, AWS Dynamo DB, AWS S3, AWS Event Bridge etc.
Raghu Ram V.
Last position:
Telco Customer Churn Prediction – End-to-End ML Pipeline at Self-Initiated Project
- Designed and implemented a full machine learning pipeline for churn prediction using the Telco dataset.
- Applied preprocessing techniques including missing value handling, categorical encoding, feature scaling, and PCA.
- Built and compared over 15 models (logistic regression, random forest, XGBoost, etc.) and evaluated them using accuracy, precision, recall, F1 score, ROC AUC, and PR AUC.
- Tuned hyperparameters with GridSearchCV, achieving 80.6% accuracy with random forest and XGBoost.
- Created visual reports (bar plots, heatmaps, radar charts) to interpret model performance and churn drivers.
- Exported reusable pipelines and trained models with joblib for deployment.
Anton K.
Last position:
Head of Overall Technical Integration NSC / Hadoop Cloud Development at IABG
Head of overall technical integration NSC (National Secure Cloud, project with approx. 60 employees).
Technical integration of all subprojects into one product, definition of interfaces and basic components of a cloud including hardware, technical architecture of the IABG platform.
Development of a Cloud Management Platform (CMP) capable of creating private/mixed clouds of any complexity based on a textual description with one click or interactively.
CMP also includes the complete hardware management lifecycle.
Kubernetes, OpenStack and Hadoop are used as the foundation.
The management layer includes Harbor, Gitea, Longhorn, Keycloak, Rancher and Jenkins, which are configured automatically.
Private cloud can run any customer workloads, including a full Hadoop layer with HDFS, Spark, MapReduce, Mesos, HBase and around 20 additional ML/DL technologies.
Hadoop worker clusters can also be installed automatically without Kubernetes on bare metal or commodity hardware.
OpenStack with Nova, Neutron, Ironic, Swift, Cinder, Ceph.
Development of a Java application Rudi: SOAP, REST, containers, DB.
Technologies: Kubernetes (K3s, Rke2, Minikube, Harbor, Gitea, Jenkins, Longhorn, Keycloak, Rancher), OpenStack (Nova, Neutron, Keystone, Swift, Ceph, Cinder, Sahara, Magnum, Kayobe, Kolla, Bigrost, Ironic), Hadoop (HDFS, Ambari, Solr, Livy, Ranger, YARN, Tez, HBase, Kafka, Hive, Zookeeper, MapReduce, Spark, Oozie, Flink), virtualization (Kubernetes (K3S), VMware, Oracle), scripting (Ansible, Puppet, Juju, Shell, Groovy, Gradle, Maven).
Kaan K.
Last position:
Computer Vision Engineer at Axulus Reply GmbH
- Computer vision engineer responsible for development of industrial vision solutions, beginning as a working student and transitioning to a full-time role in May 2025.
- Designed and implemented vehicle detection and counting models; integrated the pipeline into a cloud-deployed system (Azure) that delivers live analytics dashboards.
- Building an offline print quality assurance system that scans corrugated-board prints on production lines to detect and classify defects such as splashes, impurities and colour deviations, deploying the solution on Jetson edge devices.
- Collaborated with cross-functional teams while focusing on computer vision components, containerization, and deployment.
Vibhu K.
Last position:
Senior Product Manager at MediaMarktSaturn
- Led development and management of advanced data products and reporting solutions, driving €11M revenue in 2023. Hired and mentored a product manager to enhance product capabilities, enabling brands to gain closed-loop measurement insights.
- Defined product vision and strategy for offsite product domain globally, enabling brands to engage their most valuable customers throughout the omnichannel customer journey.
- Initiated and led data-driven martech and adtech innovations, laying groundwork for AI-powered personalization and targeted marketing across 12 countries.
Stephan S.
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Eyasu H.
Last position:
Data Scientist at Deutsche Bundesbank
- Developed web scraping scripts to extract and parse over 5000 product data from the Zalando website.
- Performed ETL processes using Apache Spark in CDSW, loaded the data into the Hadoop ecosystem (HDFS), and managed data using Hive and Impala.
- Implemented machine learning algorithms, achieving 85–90% accuracy on multi-class product classification.
- Integrated Zalando's product and price data into the dashboard with Otto and Takko for interactive visuals.
Daniel C.
Last position:
Founder & Managing Director at BotCraft GmbH
- Building the company with a focus on connectivity for IIoT and Industry 4.0, iRPA/process automation, advanced robotics and smart systems, sensors and services
- Project management and software architecture for IoT gateway development (since 2020) with protocol translation, IT/OT convergence and GRC
- Developing RPA bots for automating and monitoring industrial processes with an agent-based AI approach (since 2020)
- Implementing unsupervised clustering and anomaly detection for time series data in big data streaming pipelines (since 2021)
- Introducing a Docker-based release train for OTA updates with DevSecOps and CI/CD (since 2018)
Marius H.
Last position:
Senior Project Manager / SAFe Solution & Release Train Engineer (Lead Scrum Master) at Telefonica O2
- Led the largest agile project at Telefonica O2 (€21+ million, 11 Scrum & system teams in Germany and India, 80+ developers, 3 vendors) using SAFe, Scrum and Kanban. A showcase project at Telefonica for agile scaling.
- Scaled agile processes to a large project using SAFe.
- Delivered the project at half the cost and time compared to similar projects.
- Test management / coordination of system testing.
- Coached teams (SAFe & Scrum).
- Rollout planning/management.
Discover over 15,000 top freelancers
Statistics of experts using Keras
Aggregated from the professional profiles of matched freelancers.
Experience
17 years (Germany: 14 years)
Position duration
2 years (Germany: 2.1 years)
Positions per freelancer
13 (Germany: 9)
Top business areas
Product Development, Information Technology, Business Intelligence
Top industries
Information Technology, Automotive, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
88% (Germany: 81%)
Doctorate
18% (Germany: 21%)
Certifications per freelancer
3 (Germany: 2)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 98%)
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 Munich 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 Munich using Keras
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.
Keras 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 (94%)
- Automotive (65%)
- Banking and Finance (65%)
- Manufacturing (53%)
- Professional Services (47%)
- Education (41%)
- Healthcare (35%)
- Insurance (35%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Keras does
Keras is a high-level deep learning API for building, training and evaluating neural networks with clear Python interfaces. It supports TensorFlow and can also work with JAX and PyTorch backends, making it useful for teams that need readable model code without losing access to advanced machine learning capabilities.
Models and applications
Keras experts create and refine models for a wide range of production use cases:
- Image classification, object detection and image segmentation
- Text classification, embeddings and language modelling
- Forecasting, anomaly detection and recommendation systems
- Prototypes for generative AI and multimodal applications
They also prepare training pipelines, validation strategies and inference workflows so a model can move beyond experimentation.
Ecosystem and tooling
Strong Keras work often includes TensorFlow, Keras 3, NumPy, pandas and scikit-learn. Specialists may use TensorFlow Data pipelines, tf.data, TensorBoard, KerasTuner and model export formats such as SavedModel or ONNX. Familiarity with GPUs, cloud runtimes, containers and experiment tracking helps connect model development with reliable delivery.
When companies bring in experts
Companies usually seek freelance Keras expertise when a prototype needs to become a tested product, when model quality has stalled, or when an internal team lacks deep learning capacity. Typical assignments include:
- Selecting an architecture and preparing training data
- Improving accuracy, latency or resource usage
- Reproducing experiments and making results measurable
- Integrating inference into an application or service
In Munich, these needs can arise across manufacturing, mobility, healthcare, finance and industrial research. Remote collaboration works well when data access, documentation and review routines are defined clearly.
What strong professionals bring
Good Keras professionals understand more than layer definitions. They can assess data quality, prevent leakage, choose suitable loss functions, explain validation results and identify overfitting. They write maintainable Python, structure reusable components and document assumptions so another team can operate the training and inference process.
Assessing project fit
Ask for examples that match the model type, data constraints and deployment target of the assignment. Review how the expert measured results, handled imbalanced or sensitive data and addressed reproducibility. For collaboration in Munich, clarify whether workshops require on-site attendance, remote delivery or communication in English or German before work begins.
Frequently asked questions
Curious about Keras? Here are the answers that come up again and again.
Keras is used to build, train and evaluate neural networks for tasks such as image recognition, text analysis, forecasting and recommendation. It provides a concise API while exposing the capabilities of backends such as TensorFlow, JAX and PyTorch.
Keras focuses on a clear, high-level workflow and can run across multiple backends in its current form. PyTorch offers a more direct low-level programming style, while TensorFlow provides a broad production ecosystem; the right choice depends on model control, team skills and deployment requirements.
A strong Keras expert usually brings Python, NumPy, pandas and scikit-learn skills, along with knowledge of data preparation and model evaluation. Experience with GPUs, Docker, cloud services, experiment tracking and API integration is valuable when models must run in production.
The required background depends on the task, data quality and deployment target. A simple proof of concept may need focused model-building expertise, while production work with Keras calls for deeper knowledge of testing, reproducibility, monitoring and performance optimization.
Yes. Keras projects are often well suited to remote collaboration when repositories, datasets, environments and review practices are organized. Munich teams should define access controls, meeting expectations and whether communication is conducted in English, German or both.
Ask how the Keras expert selected the architecture, prepared the data and validated the model. Strong answers cover leakage prevention, suitable metrics, reproducible experiments and the trade-offs between accuracy, latency and operating cost.
Keras 3 is a strong option when a team wants a consistent high-level API with flexibility across TensorFlow, JAX and PyTorch backends. An expert should still confirm backend support for the required layers, tooling and deployment environment before implementation begins.
A Keras freelancer may deliver data preparation code, model definitions, training and evaluation pipelines, experiment records and deployment components. The handover should also explain configuration, dependencies, expected inputs, performance limits and how the team can retrain or monitor the model.
The average hourly rate of freelancers in Munich, Germany who have used Keras in their recent projects is 100 €, which corresponds to a daily rate of about 803 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Keras in their recent projects, 100% hold at least a Bachelor's degree, 88% hold at least a Master's degree, and 18% hold a doctorate.
On average, freelancers in Munich, Germany who have used Keras in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Munich, Germany who have used Keras in their recent projects are German (100%), English (100%), and Spanish (29%).
The most common industries among freelancers in Munich, Germany who have used Keras in their recent projects are Information Technology (94%), Automotive (65%), and Banking and Finance (65%).
The most common business areas among freelancers in Munich, Germany who have used Keras in their recent projects are Product Development (94%), Information Technology (82%), and Business Intelligence (71%).
Main locations of FRATCH Experts, who have recently used Keras
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 Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
Berlin Request a free demo
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Philipp Thomaschewski
FRATCH CEO
