CMake Expert

Clients: CARIAD, AUDI AG

• Built and deployed enterprise MLOps pipelines using Azure Machine Learning and Databricks. Reduced model release cycles by 95 percent, from four weeks to two days, through automated CI CD workflows.
• Delivered cloud native DevOps platforms for ADAS programs using Azure data services, Kubernetes, and Terraform based infrastructure provisioning.
• Designed high availability architectures with automated failover. Cut system downtime by 85 percent for mission critical energy trading platforms.
• Developed and integrated AI agents and enterprise chatbots using LangChain, AutoGPT, and GPT models. Enabled autonomous workflows and decision driven automation.
• Reduced cloud infrastructure spend by 40 percent through autoscaling strategies, spot instance usage, and policy driven resource governance across Azure and AWS.
• Partnered with Data Scientists, ML Engineers, Product Managers, and executive stakeholders to deliver large scale automotive and energy solutions.
• Implemented GitOps driven CI CD pipelines supporting automotive software delivery for over 500 engineers across distributed product teams.
• Designed and operated Kubernetes platforms on Azure AKS. Improved deployment stability and reduced rollback events by 70 percent.
• Implemented observability and monitoring stacks using Prometheus, Grafana, and Azure Monitor. Achieved 99.9 percent service availability targets.

Reporting and controlling using Power BI for a production ERP system

• Analysis of ERP data and interfaces for use in Power BI dashboards
• Evaluation and migration of existing reports (e.g. Excel) to Power BI
• Development of an authorization concept for selective data access
• Documentation and training on the use and customization of Power BI dashboards

Label: Power BI, Excel, SelectLine ERP, Microsoft SQL, SQL Server Management Studio

• Built a modular C++ 20 embedded Linux acquisition system on a Raspberry Pi, synchronizing IMU and dual-camera data streams to sub-millisecond accuracy.
• Integrated retro-reflective and contrast sensors to trigger acquisition and detect gaps between sorter rails.
• Implemented SPI & I2C sensor communication, GPIO interrupt handling with libgpiod, and CSV & JSON output.
• Designed a multi-threaded acquisition pipeline and an SPSC queue between acquisition and writer threads.
• Built a Python/HTML/CSS based web-server and validated the prototype in a DHL warehouse for defect detection.
• Documented software behavior, configuration, and results for maintainable handover and further development.

• Built and configured a highly parameterized UVM environment to validate AMBA APB subsystem.
• Developed virtual sequencers to drive synchronized, parallel master-slave sequences ensuring accurate peripheral address decoding and protocol handshake.
• Methodologies: UVM, Constrained Random Verification
• Tools: Cadence Xcelium, SimVision

• Built and verified Zynq-7000 (Zybo Z7-10) FPGA prototypes in Xilinx Vivado – AXI IP integration, bitstream generation, hardware bring-up, timing-closure checks and waveform-based debug to confirm expected RTL behaviour.
• Set up Cadence Virtuoso schematic/simulation flows and documented settings, results and methodology for reproducible experiments – supporting structured verification and research documentation.
• Wrote Python automation for log parsing, structured data reporting and result analysis; worked daily in version-controlled Linux/Git workflows.

Project: Intelligent Light Communication Software — Audi

• Analysis and clarification of system requirements with the customer and translation into software architecture and design decisions
• Architecture and implementation of CAN FD and SPI communication on NXP S32K312
• Design and development of flash bootloader, flash driver, and boot manager for secure OTA-capable updates
• Configuration of the AUTOSAR BSW architecture (Dcm, Dem, NvM, BswM, Os, Mcu, Port, Com stack, Rtc) for portability and maintainability
• Design of the crypto stack (Csm, CryIf, Crypto) for secure flash and diagnostic data; integration of the NXP HSE core and wrapper layer
• Integration of customer-specific modules (Sfd, Ivd, Npm) into the Vector AUTOSAR stack
• Definition of the memory architecture: Memmap, CMake, and linker script configuration
• Leading board bring-up for the Audi light demo platform; implementation of diagnostic routines and identifiers

Seqnaut and Sycosm (WIP) – Embedded Audio DSP & Synthesis Platform

• Embedded audio DSP framework — synthesizers, effects, drum machines; modular audio graph
• Sequencing: PianoRoll, StepGrid, MasterClock; 8-voice polyphonic synth; CLI + OSC
• Transient Detector — dual-envelope adaptive threshold, guitar attack detection
• Hardware: Teensy 4.1, custom AFE design tapping BOSS GX-100; MIDI FX integration

Label: C++23, C, Python, CMake, FreeRTOS, Teensy 4.1 (ARM Cortex-M7), Teensy Audio (Stoffregen), DaisySP, I2S/SAI, OSC, MIDI

Temporary employment

• System black-box integration tests (BBIT, IVVQ): Execution of regression, release, confirmation and conformity tests for safety-critical braking control units in the railway industry
• Software Test Application & Integration: Runtime configuration of software components and libraries, validation of interfaces, configuration dependencies and component interactions
• Test Automation (FEAT Framework): Co-development and further development of an automated test framework for test execution, reporting and result analysis
• Functional Safety (SiL4, FuSi): Ensuring compliance with safety requirements, traceability and coverage as well as conformity with EN50126/28/29
• Test Automation for Communication Components: Configuration and validation of fieldbus (CAN) and Ethernet-based TCMS data communication interfaces (TRDP and CIP)
• Requirements Analysis & Shift-Left (PTC Windchill ALM): Analysis of software and system artifacts to identify gaps, ambiguities and redundancies early in the SDLC
• Test Design & Test Case Development: Derivation of test conditions and coverage strategies and implementation of data-driven test cases (DDT) including reusable test data fixtures
• CI/CD & Automation (Python, PowerShell, Jenkins, SVN): Automation of build, test and HIL deployment processes as well as integration into CI/CD pipelines
• Test Data & Configuration Management (XML): Maintenance and adjustment of XML test vectors and system configurations with automated integration into test environments
• Non-Functional Testing: Execution of performance and load tests to assess stability and system behavior
• Agile Development & Defect Management (JIRA, Confluence): Work in Scrum teams, test coordination, review of test artifacts as well as defect tracking and root-cause analysis
• Error Analysis & Debugging (CANoe, CANalyzer): Analysis of errors and message flows across multiple system levels (application to bus)
• Model-Based Analysis (UML, Enterprise Architect): Specification of SUT/SOW and support for systematic test control
• Process & Test Documentation: Creation of integration and test documentation according to internal quality and certification requirements

PHP and React redesign of a web-based ERP system.

• Development of the header and parts of the navigation
• Development of various modules in React, such as a calendar, chat and various tables

Stellar SR6 G7 line, 32-bit Arm® Cortex®-R52+ MCU.

• MISRA-C, C99, Greenhills ARM compiler
• Dassault AUTOSAR Builder
• EB Tresos
• Sparx Enterprise Architect 16.1
• VS Code
• Python xml, lxml, NumPy and Pandas

ISO 26262, ISO 21434, hypervisor, key management, HSM. Tooling & automation. LieberLieber LemonTree + Sparx EA. Jira, Confluence, SharePoint. Git/Github. DevOps through Jenkins & Conan.

• Own the technical direction of several AI products in a product-owner capacity: shape roadmaps, guide the in-house development team, and provide oversight from concept through delivery.
• Act as the technical bridge between stakeholders, end clients, and vendors for a solutions provider (reseller and in-house products): evaluate vendor solutions against client needs, lead vendor discussions, and support sales and pre-sales with technical solution design.

• Project Title: Path Planning Module Development (Oct 2024 – Jun 2025)

• Developed path planning module using C++14 and CMake

• Implemented gRPC communication protocol between modules

• Performed unit testing using Pytest framework and Python

• Project Title: HMI Programming for Battery, Fuel Cell Electric Vehicle (Aug 2023 – Sep 2024)

• Developed HMI software for BEV/FCEV using Ruby and Crystal for backend

• Implemented frontend using Vue.js framework

• Conducted bug fixes and simulator testing

• Project Title: IFHOST CAN Bus Programming (Jan 2023 – Jul 2023)

• Programmed CAN bus software using C and C++

• Executed unit tests with Google Test framework

• Performed integration testing using CAPL in Vector CANalyzer

• Participated in onsite testing

Internal systems with regulatory and security requirements could not be used directly by AI tools for incident triage, troubleshooting, and documentation search. The goal was to securely integrate these systems through MCP while preserving existing acce...

• Leading AI development for aquaculture startup, optimising shellfish visual assessments with machine learning and computer vision.
• Development and systematic evaluation of ML/CV algorithms for shellfish condition and morphometrics, using Python, Pytorch and MLFlow.
• Analysis of model performance, including identification of failure modes and edge cases in production deployments.
• Design of annotation strategies and refinement of labelled datasets for computer vision tasks.
• Detailed analysis of system performance and communication of findings through publication-quality technical reports to investors and fellow R&D staff.
• Responsible for delivery of technical roadmap.