Edge Computing Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Edge Computing
Ananthraj Narasappa
Last position:
Founder at sprhava
Leading the end-to-end development of Edge AI-powered smart glasses for visually impaired individuals, aligning product vision with user needs and managing a cross-functional team of data scientists, Android developers, AWS engineers, and hardware specialists.
- Defined product roadmap for Edge AI smart glasses and MVP features through user research, stakeholder interviews, and competitive analysis, ensuring accessibility and real-world usability.
- Developed and validated a PoC for AI-driven cancer cell identification in PET/CT scans, collaborating with medical experts to optimize diagnostic accuracy and clinical relevance.
- Built and scaled a multidisciplinary team of 75+ engineers, interns, and designers across Germany and India, driving cross-border collaboration and iterative prototyping.
- Established strategic partnerships with NGOs, healthcare providers, and advocacy groups to embed inclusivity and patient feedback into product design.
- Drove hands-on hardware-software integration using Raspberry Pi and Jetson Nano of AI models. Initiated and nurtured relationships with suppliers, manufacturers, and ecosystem players to build scalable go-to-market plans.
- Owned critical product decisions, from prototype development to funding strategy, applying a data-informed and impact-driven mindset.
- Fostered a learning-focused culture by facilitating brainstorming sessions and continuous feedback loops between engineering and product.
Achievements:
- Public speaker: Auto.Ai 2025 (Berlin), Wearable technologies 2025 (Munich and Bangalore), MEDICA 2024 (Dusseldorf)
- WMF, Bologna, Italy (June 2024): Only AI startup to be selected from Germany as EBV hero to represent sprhava on global platform
- Medica, Germany (2024): Delivered a speech on AI smart glasses in world's largest Healthcare event.
- Wearable Technologies, Bengaluru, India (Dec 2024): I was a speaker presenting sprhava and its product.
- Venturise Global Challenge (GIM 2025, Bengaluru Palace, Karnataka): sprhava was selected as one of the 16 top startups (ESDM) to present on this global platform
- Wearable Technologies Conference 2025 EUROPE, Munich, Germany (May 2025): Delivered a talk on Edge AI at the Europe's biggest wearable tech event.
- InsurNext Köln, Germany (2025): sprhava was honoured with a booth from Cologne administration.
Thomas Langer
Last position:
Consultant for AI-driven process automation at Lumiz
AI-driven automation of purchasing on a printing company's website, including selecting delivery times, order options, ordering, payment, and uploading print data from the Lumiz Cloud.
Oussama El Allam
Last position:
Head of R&D at eXagotec GmbH
- Spearheading multidisciplinary engineering teams in the development of next-generation medical devices
- Orchestrating research initiatives and technology roadmaps to deliver innovative medical solutions
- Overseeing R&D budget and managing project portfolios from concept through to commercialisation
- Establishing strategic collaborations with clinical partners for technology validation
Daniel Carton
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)
Janusz Mazurek
Last position:
IoT Edge Computing / Self-Driving-Cars at Automotive consulting company
- Platform: Python ecosystem, RHEL 8, K10, AWS IoT Core, AWS Lambda, MLOps
- Software: Java JEE/cloud, IntelliJ IDEA, AWS IoT Core, AWS Edge and Lambda, AWS SageMaker SDK, Docker Compose, Kubernetes, OpenShift 4, Tekton, Flux, Helm charts, JSON/XML technology, Nginx, Apache Spark, OpenAI (GPT Plus, DALL-E 3, Whisper), GAN, GitHub Copilot, AI/machine and deep learning, Jupyter notebooks, TensorFlow 2, Colab, Keras API, Prometheus, Grafana, Conda, Python 3.9, PySci stack (NumPy, pandas, Scikit-learn, matplotlib)
- Responsible for webinar:
- IoT edge computing: architecture, components, resources, management
- IoT edge computing with MicroK8s, designing and creating flows/diagrams for AWS, three-step model for IoT ecosystem
- IoT processes, connectivity, data transfer and deployment, security
- Optimization of edge computing for IoT networks and services (AWS SQS queue, SNS notifications, events, analytics, buttons, device management/defender, Things Graph)
- Machine/deep learning frameworks (models, training, pipeline optimization, deployment in the cloud/at the edge (OpenShift), monitoring workloads with Prometheus and Grafana)
- Performance optimization for low latency/resilience using adaptive ML/DL/RL models for customer IoT data
- Analysis of large sensor data sets with Apache Spark, Kafka clusters
- Kasten K10 data management platform on Kubernetes multi-cluster with Helm chart, deployment, backup/disaster recovery (RTO/RPO), data lifecycle and security management
- Implementation of multilayer artificial neural network (ANN) with TensorFlow 2 and Colab for regression and classification; data analysis and provisioning for applications; development of models for testing and training, deployment of models
- Automation of business streamline processes with AI (Azure OpenAI, Discord bots/Zapier apps AI assistants (IntelliJ, GitHub Copilot))
Adithya Balaji
Last position:
Edge AI Software Engineer at Neura Robotics GmbH
- Deployed and optimized Vision-Language-Action (VLA) and diffusion policy models on NVIDIA Jetson Orin and Jetson Thor, meeting real-time inference latency targets for humanoid robot control loops.
- Built TensorRT engine pipelines (PyTorch → ONNX → TensorRT) with INT8/FP8 post-training quantization, calibration dataset design, and quantization-aware validation, reducing inference memory footprint by over 3× on Jetson without accuracy regression.
- Developed custom CUDA C++ plugins and CUDA Graphs for latency-deterministic, real-time policy execution – meeting hard runtime and memory constraints on embedded GPU targets.
- Developed an inference engine for VLA models on top of llama.cpp bringing different VLA policies under single runtime, packaging each as a single self-contained GGUF that needs no Python or PyTorch.
- Profiled and tuned GPU execution using NVIDIA Nsight Systems and Nsight Compute, identifying CUDA kernel bottlenecks, memory bandwidth saturation, and SM occupancy issues across Jetson Orin and Thor compute profiles for cross-layer performance optimization.
Discover over 15,000 top freelancers
Statistics of experts using Edge Computing
Aggregated from the professional profiles of matched freelancers.
Experience
20 years
Position duration
2.2 years
Positions per freelancer
10
Top business areas
Information Technology, Product Development, Quality Assurance
Top industries
Information Technology, Automotive, Manufacturing
Certification focus areas
Business Intelligence, Information Technology, Research and Development
Bachelor's degree or higher
83%
Master's degree or higher
67%
Doctorate
33%
Certifications per freelancer
1
Most common languages
German, English, 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 Edge Computing
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
Edge computing moves processing closer to where data is created. It is used for sensor feeds, machine control, video analysis, and other workloads that cannot wait for a distant cloud round trip. Teams also use edge to keep local operations running when links are unstable.
Typical projects
- Edge gateways for factories, stores, or vehicles
- Local inference for cameras, sensors, and smart devices
- Data filtering before cloud sync
- Fleet rollout and remote device updates
Tooling and stack
Strong specialists work across embedded systems, Linux, containers, message brokers, and cloud services. They often touch AWS IoT Greengrass, Azure IoT Edge, Kubernetes at the edge, MQTT, and device management tooling. The exact stack depends on latency needs, hardware limits, and how much logic stays local.
When to bring in help
Companies look for freelance edge expertise when they need a pilot to become a production rollout, or when a system must integrate with plants, shops, or distributed sites. It also helps when teams need short-term support for architecture, security hardening, or field deployment. In Munich, this often fits industrial, automotive, logistics, and media environments.
What strong experts do
Strong professionals think about the whole path from device to cloud. They design for offline behavior, secure updates, observability, and data flow control. They also keep the local runtime simple enough to maintain on site or remotely.
How teams work with them
Edge work usually starts with a clear site setup, a device inventory, and a list of actions that must happen locally. Good specialists document rollout steps, recovery plans, and monitoring checks so operations teams can support the system after launch. For Munich-based companies, remote collaboration is common, with site visits only when hardware or plant access is needed.
Frequently asked questions
Quick answers to the questions that come up most around Edge Computing.
Edge computing is used when data needs to be processed near the source instead of sending everything to a central cloud. That matters for video analysis, industrial control, retail sensors, connected vehicles, and other systems that need fast local responses. It is also useful when bandwidth is limited or the site must keep working during network issues.
Edge computing keeps part of the workload local, while cloud-only setups send most processing to a remote data center. The edge approach is better for low latency, local resilience, and data reduction before sync. Cloud-only can still fit reporting, long-term storage, and centralized analytics, so many systems use both.
Edge computing is the broader term, and MEC, or Multi-access Edge Computing, is a related approach often tied to telecom networks. MEC usually places services close to mobile users or network access points, while edge can also mean factories, retail sites, vehicles, or private deployments. People often search with both terms when they need local processing close to users or devices.
A strong edge computing specialist usually understands embedded systems, Linux, networking, container runtimes, and device security. Cloud integration matters too, especially for messaging, updates, identity, and observability. If the project includes cameras or sensors, experience with data pipelines and protocol work such as MQTT is important.
A simple edge computing pilot may need one strong specialist who can set up the local runtime, connect devices, and prove the data flow. A production rollout needs broader experience with security, remote updates, rollback planning, and fleet operations. The more sites and hardware types involved, the more valuable proven deployment work becomes.
With edge computing, ask what must run locally, what can stay in the cloud, and how the system behaves when the network drops. Also ask which hardware, protocols, and update process they have handled before. Clear answers here usually tell you whether the specialist can design for real operations, not just a demo.
Many edge computing tasks can be done remotely, especially architecture, software integration, and monitoring design. On-site time is useful for hardware bring-up, plant access, network checks, and deployment validation. For teams in Munich, a hybrid setup is common because some work needs physical access while most follow-up can happen online.
Look for a edge computing specialist who can explain failure modes, update strategy, and security trade-offs in plain language. Good signs are clear documentation, practical rollout plans, and examples of systems that kept working under limited connectivity. Ask how they handle observability and recovery, because that is where many edge projects succeed or fail.
The average hourly rate of freelancers in Munich, Germany who have used Edge Computing in their recent projects is 107 €, which corresponds to a daily rate of about 855 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Edge Computing in their recent projects, 83% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Munich, Germany who have used Edge Computing in their recent projects have 20 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Munich, Germany who have used Edge Computing in their recent projects are German (100%), English (100%), and French (33%).
The most common industries among freelancers in Munich, Germany who have used Edge Computing in their recent projects are Information Technology (83%), Automotive (67%), and Manufacturing (67%).
The most common business areas among freelancers in Munich, Germany who have used Edge Computing in their recent projects are Information Technology (100%), Product Development (100%), and Quality Assurance (100%).
Main locations of FRATCH Experts, who have recently used Edge Computing
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.
Countries:
Berlin Hamburg 
Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
