Computer Vision Experts in Munich
in minutes from over 15,000 CVs with the power of AIHire experts who turn images and video into detection, tracking, inspection, and measurement systems. They work with OpenCV, model training, and deployment for edge or cloud setups. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Computer Vision
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Giuseppe Abrignani
Last position:
Embedded Software Developer at Inheco
- AI Integration (LLM & RAG): Design and build of an internal intelligent RAG system (Retrieval-Augmented Generation) based on LLMs, n8n, and vector data for the automated analysis of technical documents and error logs.
- Design & Implementation: Design of a robust RS-232/UART communication interface for an SBC-based embedded device to control medical shaker systems.
- Architecture & Protocol Design: Implementation of a highly maintainable software structure (OOP, SOLID) and definition of hardware-close, resilient communication protocols including multithreading and advanced error handling.
- Quality Assurance & DevOps: Test automation using xUnit, integration tests directly on the hardware target, and maintenance of technical documentation according to strict medical technology standards via Azure DevOps.
Label: C#, .NET, LLMs, RAG, n8n, RS-232, UART, Multithreading, async/await, xUnit, gRPC/protobuf, Blazor, MudBlazor, EF Core, Visual Studio 2026, Azure DevOps
Valery Khamenya
Last position:
Sr. Data Scientist & Engineer at Virtual Minds
- Development of high-performance ad distribution via auction
- Holistic (multi-campaign & multi-channel) advertisement placement optimization
- Algorithmic optimization for NP-Hard/NP-e
- Multiple Knapsack Problem with constraints
- Online estimation of parameters in stochastic environments
Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker
Anton Lorani
Last position:
Freelance Software Developer at Anton Lorani Software&AI Engineering
Michael Boldasov
Last position:
Scrum Master, Project Manager at GP Solutions DMCC
- Participated in the Riyadh Public Transport (KAPT) project introducing public transportation in Riyadh, supporting multimodal journeys combining bus, metro, car on demand.
- Worked via Thiqah and partnered with Andersen to refactor the mobile MaaS application DARB into a new microservices architecture under SCRUM framework, successfully completing Phase 1.
- Facilitated a team of 40 developers across Android, iOS, Web, Java, DevOps, architecture, analysis, and QA.
- Moderated Scrum events and communicated with the client, proactively reporting on project deadlines, scope, and challenges.
- Coordinated cross-team efforts between Thiqah specialists and GPS development teams, managing Jira and Azure DevOps trackers.
- Supported and improved Scrum processes throughout the project.
- Due to Thiqah’s takeover by Elm, subsequent phases were handled entirely in Saudi Arabia with GPS providing IT consulting.
- Tools: Azure DevOps, Jira, Confluence, Draw.IO, ChatGPT
Raghu Ram Vadali
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.
Tobias Bauernfeind
Last position:
Lead XR Project at BMW Group
- Showcasing the world's first fully immersive AR glasses experience in a moving car at CES 2024.
- Speaker about augmented reality at international conferences (e.g. the AR Ride Concept @ Unite 2024).
- Lead a 12-person interdisciplinary software team developing Android head-unit integrations, navigation & ADAS UI, and embedded software.
- Define technical direction, drive cross-domain architecture and integration, and mentor engineers across Android, UI/UX and embedded stacks.
- Oversee a small fleet of test vehicles for validation, tests, and data collection.
Mevlüt Yıldırım
Last position:
Project at Physical Adversarial Attacks Using Fan-Based Holographic Projections
- Planned and executed black-box adversarial testing of traffic-sign computer-vision pipelines; produced a threat model and attack-surface analysis for safety-critical scenarios
- Built a programmable hardware proof of concept using a holographic POV fan and a repeatable test harness to run real-time experiments and collect evidence for vulnerability assessment
- Quantified misclassification across lighting, distance, and angle, achieving up to 90% untargeted misclassification; delivered steps to reproduce, PoCs, and prioritized mitigations, and documented limitations and residual risk
Stephan Sahm
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)
Stephan Baier
Last position:
Freelance Data Scientist at Baier Data & AI Consulting
Kerstin Burgen
Last position:
Reporting and analytics for HR at Apobank
- Designing and implementing an interactive evaluation system for top executives to rate core competencies such as goal orientation, team culture, and strategic alignment.
- Integrating control mechanisms to enforce feedback limits and store evaluations in a central system to ensure data integrity.
- Optimizing data processing for personnel development by automating the merging of various information sources for form letters.
- Implementing technical data preparation and analysis for the annual compensation comparison in the financial sector.
- Developing automated processes for data preparation in Excel using Power Query, ensuring data integrity and anonymization according to data protection requirements.
- Automating personnel cost analysis by developing a solution to process data from the Paisy system into an SAP-compatible Excel file.
- Creating test cases, user documentation, and test plans for all developed systems.
- Technologies: Power Query, MS Office 2016 (Word, Excel, PowerPoint), Paisy, SAP, VBA.
Roumaissa Troudi
Last position:
Master’s Thesis: AI-Based Analysis of 2D and Exploded View Drawings at Technical University of Munich
- Developed an end-to-end AI pipeline for analyzing 2D exploded-view drawings using computer vision and deep learning models.
- Integrated YOLO-based object detection (Bounding Boxes, Post-Processing, Overlap Handling) for accurate part and callout detection.
- Applied the Segment Anything Model (SAM) for fine-grained segmentation and separation of individual components.
- Implemented OCR and feature extraction modules, and compared Vision Language Models (VLM) and traditional computer vision approaches in terms of accuracy, runtime, and scalability.
Gabriel Baude
Last position:
Applied Research and Design at Privacy-First Family Tech Sabbatical
- Initiated mission-driven sabbatical: Developing privacy-first solutions for international family communication challenges, researching advanced encryption methods, kid-proof authentication alternatives, and censorship-resistant, immutable systems to create genuinely personal services respecting user privacy by design, not policy.
- Addressed language barriers: Built and launched Tiptap, an offline-first communication enhancement tool enabling seamless parent-child interaction across language barriers with a privacy-by-design architecture.
- Stimulate presence memory: Designed and architected Pebbble, a zero-knowledge privacy system using NFC-enabled physical stones as decryption keys to maintain censorship-resistant voice presence via IPFS-distributed audio content.
Vasco Almeida
Last position:
AI Research Intern – Generative AI at BMW AG
- Designed and implemented multi-modal entertainment toolchains that combine passenger input, vehicle context, large-language models (text-to-text and speech-to-speech) and image generation models to deliver more interactive and immersive in-car experiences.
- Built and orchestrated tools for LLM-based agents, covering session management, background task execution, dynamic user interactions and persistent application state.
- Investigated multi-agent orchestration frameworks for in-car environments, evaluating communication protocols and architectural strategies for coordinated and reliable agent behavior.
Narges Dastanpour Hosseinabadi
Last position:
Research Assistant at Munich University of Applied Sciences
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.
Discover over 15,000 top freelancers
Statistics of experts using Computer Vision
Aggregated from the professional profiles of matched freelancers.
Experience
12 years
Position duration
1.8 years (Germany: 2 years)
Positions per freelancer
8 (Germany: 7)
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Manufacturing, Education
Certification focus areas
Business Intelligence, Information Technology, Project Management
Bachelor's degree or higher
96% (Germany: 97%)
Master's degree or higher
96% (Germany: 85%)
Doctorate
25% (Germany: 14%)
Certifications per freelancer
2
Most common languages
English, German, French
Speak two or more languages
100%
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 Munich 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 Munich using Computer Vision
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 it covers
Computer vision turns images and video into structured results. It is used for object detection, image classification, pose estimation, OCR, defect inspection, and scene understanding. Companies bring in specialists when raw visual data needs to become reliable decisions.
Typical work
- Build pipelines for image capture, labeling, training, and validation
- Tune models for detection, segmentation, tracking, or recognition
- Connect vision output to production systems and alerts
- Optimize inference for edge devices, cameras, or cloud services
Tooling stack
Strong professionals usually work with OpenCV, PyTorch, TensorFlow, and common annotation tools. They understand camera calibration, data augmentation, model evaluation, and deployment constraints. In Munich, this often matters for manufacturing, mobility, robotics, and industrial quality control.
When to bring in help
You usually need freelance expertise when a proof of concept must become a stable system, when a model fails on real-world footage, or when an existing pipeline needs performance work. Companies also hire specialists for short projects, audit work, and team support when internal skills are thin.
What strong specialists do
Good computer vision specialists think about data quality first. They test lighting, angles, motion blur, class imbalance, and false positives before chasing model complexity. They also write clear handover notes so the system can be maintained after delivery.
Fit for your project
- You need image or video analysis, not just generic AI
- Your data comes from cameras, sensors, or inspection lines
- You need on-site coordination in Munich or secure remote delivery
- You want a specialist who can work across data, models, and integration
Frequently asked questions
Not sure where to start with Computer Vision? These answers cover the essentials.
A strong Computer Vision specialist turns visual data into usable outputs such as labels, detections, counts, masks, or alerts. That can mean building an inspection pipeline, improving recognition on camera feeds, or preparing models for production use. The work usually spans data prep, model training, testing, and deployment.
Computer Vision is the better choice when rules alone cannot handle variation in lighting, angle, motion, or object shape. Traditional image processing can still help with thresholds, filters, and calibration, but it is limited when the scene changes often. Many projects use both, with classical steps supporting the model pipeline.
OpenCV is a core tool, but by itself it is rarely enough for a full production system. Most real projects also need model training, data labeling, evaluation, and integration with downstream software or hardware. A good specialist knows where OpenCV helps and where a learning-based approach is needed.
A useful Computer Vision expert often brings Python, data handling, model evaluation, and deployment experience. For many projects, edge inference, camera systems, MLOps, and domain knowledge matter just as much as the model itself. In industrial settings, signal flow and hardware constraints are often part of the job.
The best computer vision projects start with clear examples, camera specs, target outputs, and failure cases. A specialist can work with incomplete material, but they need enough context to judge data quality and define a realistic approach. Without that, the team risks building for the demo instead of the real environment.
Many CV tasks can be done remotely if the data, environment, and security rules are clear. On-site work is helpful when cameras must be installed, lighting must be checked, or the system runs on a production line in Munich. Hybrid collaboration is common for projects that mix software and hardware.
Look for concrete project results, not broad claims. A strong Computer Vision professional can explain data choices, error types, evaluation metrics, and why a model behaved a certain way in real footage. They should also be able to describe deployment limits, not just training results.
Machine vision usually refers to vision systems used in industrial or automated environments, often with cameras, sensors, and inspection goals. Computer Vision is broader and includes consumer apps, robotics, medical imaging, retail analytics, and many other use cases. The skills overlap heavily, so many specialists work across both terms.
The average hourly rate of freelancers in Munich, Germany who have used Computer Vision in their recent projects is 90 €, which corresponds to a daily rate of about 719 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Computer Vision in their recent projects, 96% hold at least a Bachelor's degree, 96% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Munich, Germany who have used Computer Vision in their recent projects have 12 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Munich, Germany who have used Computer Vision in their recent projects are English (100%), German (93%), and French (26%).
The most common industries among freelancers in Munich, Germany who have used Computer Vision in their recent projects are Information Technology (81%), Manufacturing (52%), and Education (48%).
The most common business areas among freelancers in Munich, Germany who have used Computer Vision in their recent projects are Information Technology (100%), Product Development (96%), and Research and Development (89%).
Main locations of FRATCH Experts, who have recently used Computer Vision
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 
Cologne 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
