Sensor Fusion Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Sensor Fusion
Yimeng Wang
Last position:
R&D Software Engineer at Advantest
- Development and maintenance of hardware drivers in C++
- Conducting unit and integration tests to ensure code quality
- Debugging and fixing issues with the hardware team and FPGA team
- Defining and developing software concepts and coordinating with the software architect
- Expanding test automation to improve efficiency
- Research and development of algorithms to improve existing codebases (runtime, memory usage, accuracy)
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.
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.
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)
Ehsan Zibaei
Last position:
Freelance Robotics Software Engineer at Independent Contractor
- Developed and deployed custom ROS2 nodes for real-time LiDAR-IMU fusion using R3Live++ on ARM64 hardware (Docker, CMake)
- Configured IMU, camera, and LiDAR drivers for proper data timing and formats to enable real-time 3D mapping with R3Live
- Built complete simulation stack for quadrotor UAVs: Ardupilot SITL + ROS2/DDS + Gazebo Harmonic + YOLOv8 detection
Madhava Narayanappa
Last position:
Function Developer ADAS at Continental Automotive GmbH through Ferchau GmbH
- Project: Sensor fusion application for traffic participant detection
- Software frameworks: C++ (11,14), Python, Visual Studio, MTS, Qt, GitHub, Jenkins, JIRA, Confluence, Conan, CAN, RTOS, DOORS, CMake
- Refactored and adapted sensor fusion algorithms by processing sensor data (camera and radar) for ACC and EBA as per requirements
- Handled system test issue reports in JIRA
- Tuned Kalman filters and introduced new features to enhance tracking
- Adapted architecture, detailed design (UML) and simulation tool (Qt)
- Conducted unit testing, code reviews and static code analysis in compliance with MISRA standards
- Conducted regression testing to validate software, involved in software releases (CI/CD), KPI evaluation by testing NCAP scenarios
- Flashed ADAS software to target vehicles, used UDS protocol and OBD-II tools for diagnostics and verification
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 Sensor Fusion
Aggregated from the professional profiles of matched freelancers.
Experience
10 years
Position duration
2.5 years
Positions per freelancer
5
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Automotive, Information Technology, Manufacturing
Certification focus areas
Information Technology, Logistics, Quality Assurance
Bachelor's degree or higher
100%
Master's degree or higher
100%
Doctorate
14%
Certifications per freelancer
1
Most common languages
English, German, Spanish
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 Sensor Fusion
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 does
Sensor fusion combines signals from multiple sensors into one consistent view of the world. It is used in robotics, autonomous systems, mobile devices, industrial inspection, and vehicle perception when a single sensor is not enough.
Typical work
- Merge IMU, camera, radar, lidar, and GNSS inputs
- Estimate pose, motion, position, and object state
- Design filtering and tracking pipelines
- Handle calibration, time alignment, and latency
- Validate results in simulation and field tests
Core methods
Strong professionals know more than one fusion strategy. They choose between Kalman filters, extended Kalman filters, particle filters, Bayesian methods, and learned approaches depending on noise, drift, and real-time needs.
Tooling and stack
A solid Sensor Fusion setup often sits in Python, C++, ROS, MATLAB, or embedded environments. The work also touches coordinate frames, sensor models, synchronization, and test data from road, lab, or factory settings.
When companies bring help
Teams usually look for freelance expertise when a fusion pipeline is unstable, calibration is off, or a prototype needs to move into production. In Munich, this often comes up in mobility, robotics, industrial automation, and research-heavy product teams.
What good specialists deliver
Good experts explain assumptions clearly and measure error, drift, and robustness. They write maintainable code, document calibration steps, and make sure the fused output is usable for planning, control, or perception. The best Sensor Fusion work is precise, testable, and built for the sensor suite in front of it.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Sensor Fusion.
Sensor Fusion is used to combine readings from cameras, IMUs, radar, lidar, GNSS, and other sources into one more reliable estimate. Companies use it for localization, object tracking, navigation, and perception in robotics, vehicles, drones, and industrial systems. It matters most when each sensor has blind spots or noise.
Sensor Fusion is a specific form of data fusion focused on physical sensors and time-based measurements. Data fusion is broader and can include business data, logs, or other non-sensor inputs. In practice, searchers often use both terms, but sensor fusion usually points to real-time estimation and tracking.
A strong Sensor Fusion specialist should know Kalman filters, extended Kalman filters, particle filters, and basic Bayesian reasoning. For modern systems, knowledge of sensor models, calibration, and time synchronization matters just as much. If the project uses learning-based perception, that is often an extra plus.
Sensor Fusion work often sits next to robotics, computer vision, control systems, and embedded software. Experience with ROS, Python, C++, MATLAB, and simulation tools is useful because the fusion layer rarely lives alone. A good specialist also understands coordinate transforms and measurement noise.
A small prototype may only need a Sensor Fusion specialist who can review assumptions and set up a basic filter correctly. Production systems need deeper experience with calibration, failure modes, real sensor data, and testing under edge cases. If the output drives safety-critical behavior, senior-level judgment is important.
Yes, many Sensor Fusion tasks can be done remotely if data, test logs, and simulation access are available. On-site work is useful when a specialist must inspect hardware, tune sensors, or run field tests with the team. In Munich, hybrid collaboration is common for robotics and mobility projects.
Look for clear reasoning, not just working code. A strong Sensor Fusion expert can explain sensor assumptions, show how they handle drift and latency, and demonstrate validation on real or simulated data. Good documentation and reproducible tests are strong signs of quality.
Ask which sensors are involved, what the fused output must support, and how success will be measured. A serious Sensor Fusion specialist will also ask about sample rates, calibration data, time sync, and whether the system must run in real time. That tells you whether they can fit the project.
The average hourly rate of freelancers in Munich, Germany who have used Sensor Fusion in their recent projects is 84 €, which corresponds to a daily rate of about 671 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Sensor Fusion in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Munich, Germany who have used Sensor Fusion in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 2.5 years.
The most common languages among freelancers in Munich, Germany who have used Sensor Fusion in their recent projects are English (100%), German (86%), and Spanish (14%).
The most common industries among freelancers in Munich, Germany who have used Sensor Fusion in their recent projects are Automotive (86%), Information Technology (57%), and Manufacturing (57%).
The most common business areas among freelancers in Munich, Germany who have used Sensor Fusion 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 Sensor Fusion
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
