Convolutional Neural Network Experts in Berlin
in minutes from over 15,000 CVs with the power of AI.Hire experts who design and tune CNN pipelines for image classification, object detection, and defect inspection, and who work with TensorFlow, PyTorch, and model evaluation. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Convolutional Neural Network
Hamza Khan
Last position:
Academic Research Contributor in Health Sector (Volunteer)
- Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
- Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.
Dilip Goswami
Last position:
Freelance Computer Vision Consultant at Spiral Physical Therapy Inc.
- Developing methods for monocular 3D facial reconstruction and personalized geometric modelling from mobile imagery
- Building learning-based approaches for facial shape estimation, video-based facial analysis, and privacy-preserving visual learning
Unnikuttan Velamkudy Vijayan
Last position:
Managing Director (Co-Founder) at AathmaSignals
- Spearheading investor outreach and partnership development as founding MD, building the business case and technical narrative needed to attract initial funding and strategic collaborators in the digital health space
- Designing multi-agent AI systems for autonomous biosignal analysis, orchestrating LLM-based reasoning pipelines with domain-specific medical context to enable intelligent, clinical decision support
Julien Look
Last position:
MLOps Engineer at SAMGEN
- Building and scaling cloud infrastructure on GCP to support a SaaS platform for industrial clients
- Designing and implementing a data-driven DevOps pipeline for streamlined deployment and CI/CD workflows
- Collaborating with Data Science team on MLOps workflow to automate integrated retraining
Sara Ali
Last position:
Research Associate and Data Scientist at National Center of Robotics and Automation - Condition Monitoring Lab
- Developed ASR and TSR-based speech processing pipelines on AWS, enabling efficient feature extraction and scalable deployment for speech and text analytics.
- Built a Multimodal Speech Emotion Recognition system combining NLP and deep learning (audio + text), achieving 98% accuracy and supporting real-time, cloud-based inference.
- Designed and optimized end-to-end model training and evaluation workflows using AWS services (S3, EC2, Lambda) to ensure performance, reliability, and reproducibility.
- Created and deployed interactive, user-friendly dashboards for data visualization and insight generation, supporting research teams and management in data-driven decision-making.
Tushar Rao
Last position:
Research Assistant/Master Thesis at Otto-von-Guericke Universität Magdeburg
- Performed qualitative and quantitative analysis of extracted findings, categorizing themes, evaluating methodologies, and assessing study quality and reliability.
- Produced research reports and evidence summaries communicating key trends, gaps, and opportunities to academic advisors or cross-functional teams.
- Presented findings through well-structured visualizations, tables, and narrative summaries to support decision-making and guide future research directions.
Arju Chaturvedi
Last position:
AI-Powered Resume Evaluator at Personal Portfolio
- Employed advanced natural language processing to analyze resume content, identifying key skills and experience relevant to specific job descriptions.
- Provided actionable recommendations for resume improvement, highlighting content gaps and suggesting optimization strategies.
- Evaluated and enhanced compatibility with Applicant Tracking Systems through keyword analysis and format optimization.
Discover over 15,000 top freelancers
Statistics of experts using Convolutional Neural Network
Aggregated from the professional profiles of matched freelancers.
Experience
10 years (Germany: 11 years)
Position duration
1.2 years (Germany: 1.8 years)
Positions per freelancer
8 (Germany: 7)
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Healthcare, Education
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100% (Germany: 98%)
Master's degree or higher
71% (Germany: 87%)
Certifications per freelancer
1 (Germany: 2)
Most common languages
German, English, Hindi
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 Berlin 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 Berlin using Convolutional Neural Network
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 CNNs do
Convolutional Neural Networks, often called CNNs or ConvNets, are built for pattern-heavy data such as images and video frames. They help systems recognize objects, classify scenes, segment images, and detect visual defects. Teams also use them for medical imaging, retail analytics, and quality control.
Core building blocks
A strong CNN specialist works with layers that capture edges, textures, shapes, and higher-level features. Typical work includes pooling, normalization, transfer learning, and model fine-tuning.
- Define input shape and label strategy
- Choose a backbone and train loop
- Tune augmentation and regularization
- Measure accuracy, recall, and false positives
Tools and stack
CNN work often sits in Python projects with TensorFlow, Keras, or PyTorch. Professionals also handle OpenCV, NumPy, annotation tools, GPU training, and export formats such as ONNX for deployment. In Berlin, these skills often support product teams, industrial imaging, and research groups.
When companies bring in help
Freelance expertise is useful when a model must move from prototype to reliable production. Companies look for specialists when labels are noisy, training is unstable, or a current model misses real-world cases.
- Improve a baseline model
- Debug training and inference issues
- Adapt a model to a new image domain
- Prepare deployment for edge or cloud use
What strong specialists deliver
Good CNN professionals write clean experiments, explain trade-offs, and know how to test models against business goals. They watch for overfitting, class imbalance, and data leakage, then make practical choices that hold up outside the lab. Clear documentation and reproducible training steps matter as much as the final model.
Berlin project fit
Berlin teams often need CNN expertise for startups, manufacturing, media, logistics, and healthcare imaging. Remote collaboration works well for most model work, but on-site access can help when data lives in a secure lab or production line. Clear English is usually enough, while German can help with internal stakeholders and domain review.
Frequently asked questions
Not sure where to start with Convolutional Neural Network? These answers cover the essentials.
A Convolutional Neural Network is used to read visual patterns in images and video. Companies use it for classification, detection, segmentation, inspection, and other tasks where spatial structure matters. It is a strong fit when rules-based image processing is too rigid.
Yes. CNN is the common abbreviation, and ConvNet is a widely used short name for the same model family. You may also see the full term, Convolutional Neural Network, in research notes and project documents.
A Convolutional Neural Network is often easier to start with for structured visual tasks and smaller data sets. Vision Transformers can shine on large-scale vision problems, but they may need more data and tuning. Many teams still choose CNNs for stable baselines, fast inference, and simpler deployment.
A strong Convolutional Neural Network specialist usually knows Python, TensorFlow or PyTorch, OpenCV, and basic statistics. Data labeling, augmentation, experiment tracking, and model export also matter. For production work, deployment and monitoring skills are important too.
A Convolutional Neural Network project moves faster when the expert has access to sample data, label rules, and the business goal behind the model. They should also see how the output will be used, such as triage, search, or quality checks. With that context, they can choose the right architecture and evaluation plan sooner.
Yes, most Convolutional Neural Network work can be done remotely, especially data review, training, and evaluation. On-site work is mainly useful when images come from secure equipment, a lab, or a production floor in Berlin. Hybrid setups are common when subject-matter review needs to happen in person.
Look for clear experiments, sensible evaluation metrics, and explanations that connect model results to the real use case. A strong Convolutional Neural Network expert can describe failure modes, show how they handled imbalance or noise, and explain why a model choice fits the data. Reproducible code and clean documentation are good signs.
A Convolutional Neural Network is often the better choice when visual patterns are complex and hand-built rules break down. Classical computer vision can still work for simple, stable tasks with clear edges or fixed conditions. The right expert will compare both approaches before committing to a training plan.
The average hourly rate of freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects is 68 €, which corresponds to a daily rate of about 545 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects, 100% hold at least a Bachelor's degree and 71% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 1.2 years.
The most common languages among freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects are German (100%), English (100%), and Hindi (29%).
The most common industries among freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects are Information Technology (100%), Healthcare (71%), and Education (57%).
The most common business areas among freelancers in Berlin, Germany who have used Convolutional Neural Network in their recent projects are Information Technology (100%), Product Development (100%), and Research and Development (100%).
Main locations of FRATCH Experts, who have recently used Convolutional Neural Network
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 
Munich Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
