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I am hiring for Senior Machine Learning Engineer to lead the development of cutting-edge AI models for Occupant and Driver Monitoring Systems (OMS/DMS).  Job Title: Senior Machine Learning Engineer Location: Munich (Hybrid 1-3 days in office per week) Key ResponsibilitiesComputer Vision & ML Development: Design and develop models for:Object Detection (Person Detection, Child Seat Detection, Gaze Detection)Pose Estimation (Head Pose Estimation, Facial Landmark Detection)Classification & Localization (e.g., identifying and locating phones or objects within the vehicle)Technical Leadership:Lead the technical direction of projects, including setting milestones and ensuring deliveryPlan and review development cycles, mentor team members, and guide research effortsEmbedded Systems Integration:Optimize and port computer vision models to embedded platformsEnsure model compatibility, performance, and efficiency on target hardwareFull ML Pipeline Ownership:Oversee data acquisition, preprocessing, and annotationManage training pipelines and model iteration cycles RequirementsPhD (or equivalent research experience) in Machine Learning, Computer Vision, or a related fieldStrong hands-on experience with Python (essential) and familiarity with C++ (nice to have)Proficient in PyTorch, TensorFlow, and OpenCVProven track record of deploying ML models to embedded systems Nice to HaveExperience with Driver Monitoring Systems (DMS)Experience with GenAI i.e. Diffusions, GANs, etc…

Our client is developing Level 4 certifiable autonomous driving systems for public transport— made in Germany. They specialize in legally compliant, explainable AI technology inspired by cognitive neuroscience. Their unique system is capable of making logical, transparent decisions in complex road scenarios without relying on black-box models. Motor AI’s vision is to enable individual, autonomous mobility for everyone, with a focus on safety, accessibility, and scalability. As a DevOps Engineer, you will build and maintain the infrastructure that powers their development, testing, and deployment pipelines—ensuring reliability, scalability, and security at every stage of the autonomous driving stack. Responsibilities: • Design, implement, and maintain CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions) for continuous integration and delivery of our autonomous driving software. • Manage containerization (Docker, Podman) and orchestration using Kubernetes for scalable, resilient environments. • Automate infrastructure with tools like Terraform, Ansible, or Puppet using Infrastructure as Code (IaC) best practices. • Set up and monitor system performance with tools such as Prometheus, Grafana, ELK Stack, or Datadog. • Manage cloud infrastructure across AWS, Azure, or GCP for deployment and scaling of services. • Implement and maintain observability, incident response, and deployment strategies (e.g., Blue/Green, Canary). • Ensure compliance with DevSecOps principles, including secrets management and system hardening. Requirements: • Experience with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions. • Proficiency in containerization and orchestration with Docker and Kubernetes (K8s). • Hands-on knowledge of Infrastructure as Code tools (Terraform, Ansible, Puppet). • Familiarity with monitoring and logging solutions (Prometheus, Grafana, ELK Stack). • Experience working with cloud platforms (AWS, GCP, Azure) and Linux server administration. • Strong scripting skills (Bash, Python, YAML) and understanding of Git and GitOps workflows. • Solid foundation in networking fundamentals (DNS, HTTP, SSL, TCP/IP). • Experience with DevSecOps, incident management, and deployment strategies for zero downtime. •Knowledge of RAID storage and load balancing is a plus. Note: We’re open to candidates with varying levels of experience across cloud providers or orchestration tools if you bring strong fundamentals and a willingness to learn. Why you should join us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects at every stage of development. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. • Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district.

Our client pioneering Level 4 certifiable autonomous driving technology tailored for local public transport—built on a foundation of German precision and cutting-edge cognitive AI. Their mission is to connect people, no matter where they are, by delivering intelligent, explainable, and legally certifiable autonomous mobility systems. Through neuroscience-inspired decision-making and a full-sensor stack, their autonomous driver sets new standards for safety, transparency, and scalability. As a System Architect, you will design and define the complex systems that power our AI-driven autonomous driving stack, from edge computing to cloud-native integrations. Responsibilities: • Design and implement real-time embedded systems and edge computing architectures for autonomous vehicle platforms. • Develop and integrate vehicle networks including CAN, LIN, FlexRay, and Automotive Ethernet for robust in-vehicle communication. • Define and maintain software and hardware system architecture for AI/MLbased perception and decision-making pipelines. • Lead the development of service-oriented architectures (SOA, microservices) and support their deployment using containerization tools such as Docker and Kubernetes. • Ensure compliance with functional safety and cybersecurity standards such as ISO 26262 and ISO/SAE 21434. • Architect and implement systems that support OTA updates, V2X communication, and DevOps pipelines (e.g., GitLab CI, Jenkins). • Bridge embedded, edge, and cloud infrastructure, leveraging platforms like AWS, GCP, or Azure for cloud-to-car functionality. Requirements: • Proven experience with embedded systems and real-time system architectures. • Expertise in sensor fusion, particularly with Radar, LiDAR, and Camera systems. • Strong background in high-performance computing (HPC) and edge AI applications in vehicles. • Familiarity with cloud-native architectures and cloud platforms (AWS, Azure, or GCP). • Experience with containerization (Docker, Kubernetes) and DevOps/CI-CD pipelines. • Knowledge of Software-Defined Vehicles (SDV) and AUTOSAR (Classic & Adaptive) platforms. • Understanding of vehicle communication protocols and V2X technologies. • Strong grasp of system-level cybersecurity and functional safety requirements. • Experience with ROS/ROS2 is a plus. • Excellent communication skills and ability to collaborate across hardware/software teams. Note: Certain expertise areas such as AUTOSAR or specific cloud platforms can be flexible based on the candidate’s strengths and learning capabilities. Why you should join us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects at every stage of development. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. • Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district.

Our client is pioneering Level 4 certifiable autonomous driving solutions, tailored for public transport and designed with safety at the core. By leveraging cognitive intelligence and cutting-edge AI based on German research, they create autonomous systems that make logical, explainable decisions in complex road scenarios. Their mission is to enable sustainable, safe, and scalable mobility solutions, ensuring that autonomous technology can connect people everywhere—especially in rural areas and underserved communities. As a SOTIF Expert, you will play a key role in ensuring the safety of our autonomous systems. You will be responsible for analyzing potential risks, validating safety concepts, and applying your deep knowledge of safety standards to develop systems that meet the highest safety requirements. Responsibilities: • Provide in-depth expertise on SOTIF (ISO/PAS 21448), ISO 26262 (Functional Safety), and safety-critical systems in the context of autonomous driving. • Lead Hazard and Risk Analysis (HARA) processes and SOTIF Safety Goals development to ensure compliance with the highest safety standards. • Design and implement safety concepts for ADAS/AD systems, focusing on the behavioral safety of autonomous functions. • Conduct validation and verification of safety-relevant systems through testing in real and simulated environments. • Identify unknown risks and manage scenarios involving “unknown unknowns” within the context of autonomous driving. • Work closely with system architects and developers to ensure safety requirements engineering is integrated into the design and development of the autonomous driving system. • Apply methodologies such as FMEA, FTA, STPA for safety analysis and develop test cases for SOTIF validation. Requirements: • Extensive experience with SOTIF (ISO/PAS 21448) and ISO 26262 (Functional Safety) standards. • Strong background in Hazard and Risk Analyses (HARA) and the creation of SOTIF Safety Goals. • Expertise in validating safety-critical systems and identifying unknown risks in autonomous driving contexts. • Experience with tools like DOORS, Polarion for requirements management, and MATLAB/Simulink for modeling and simulation. • Proficiency in Python and/or C++ for analysis and test automation. • Familiarity with CAPL, CANoe, and other tools for vehicle communication and testing. • Experience with simulation tools such as IPG CarMaker, dSPACE, or SCANeR. • Strong understanding of virtual validation and sensor failure analysis (camera, LiDAR, radar). • Experience applying FMEA, FTA, and STPA for safety analysis in autonomous driving. • Excellent communication skills, with a collaborative mindset for working with cross-functional teams. Note: Familiarity with Model-Based Systems Engineering (MBSE) is a plus. Why you should join us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects at every stage of development. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. •Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district.

Our client is building certifiable Level 4 autonomous driving systems for local public transport—designed and developed in Germany. Their mission is to connect people, no matter where they live, by enabling self-determined and sustainable mobility through cognitive artificial intelligence. Their unique approach, rooted in neuroscience and explainable AI, enables real-time decision-making in complex and unknown traffic scenarios—without relying solely on data from millions of kilometres of driving. As a Scene Understanding Engineer, you will play a vital role in shaping the perception and cognition systems that allow our autonomous driver to interpret and interact with its environment. Responsibilities: • Develop and enhance scene understanding algorithms for complex, real-world environments. • Design and implement modular, explainable systems that integrate sensor data and support perception and localization modules. • Lead small development teams and contribute to overall system architecture and software integration. • Collaborate with cross-functional teams to ensure seamless interaction between perception, planning, and control modules. • Participate in testing and validation of autonomous systems in both simulated and real-world environments, including field testing. • Support the certification process by developing traceable and explainable logic for perception systems. Requirements: • Degree in Robotics, Localization, Sensor Fusion, or a related field. • Strong software development skills with C++ and Python. • Proven experience in leading small engineering teams and managing complex software systems. • Solid understanding of model-based design and modular system architecture. • Experience with robotics or autonomous vehicle platforms in real-world or motorsport environments. • Good grasp of deep learning principles, especially as applied to perception. • Fluent in written and spoken English. • Willingness to travel for testing and collaborative projects. • Familiarity with sensor fusion, object fusion, and localization algorithms is a plus. Note: Some technical experience (e.g., deep learning, motorsport testing, or control systems) may be negotiable depending on your background and ability to learn quickly. Why you should join us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects at every stage of development. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. • Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district.

Our client is building the next generation of autonomous vehicle systems—ones that don’t just detect the world, but understand it. Inspired by neuroscience and built on advanced AI, they're developing a cognition-first approach to perception that allows our vehicles to reason about complex urban environments. As a Perception Engineer, you'll contribute directly to the real-time perception stack— building systems that transform raw sensor data into a deep understanding of the driving scene. Responsibilities: • Design, develop, and optimize real-time perception algorithms for autonomous driving using data from LiDAR, radar, cameras, and ultrasound. • Implement advanced sensor fusion pipelines combining multi-modal data for robust object detection and classification. • Build and fine-tune deep learning models for semantic segmentation, instance segmentation, and object tracking (e.g., YOLO, Mask R-CNN, DeepSORT). • Process and analyze 3D point cloud data for spatial reasoning and environmental understanding. • Work with tracking and filtering methods such as Kalman filters and Extended Kalman Filters (EKF) for dynamic object tracking. • Integrate and calibrate perception sensors with high-precision requirements (camera, radar, LiDAR). • Simulate and test perception systems in virtual environments (e.g., Carla, AirSim) and validate them in diverse real-world conditions (night, rain, fog). • Collaborate closely with SLAM, mapping, and planning teams to ensure consistent scene representation and performance. Requirements: • Solid background in computer vision and deep learning (CNNs, RNNs, 3D CNNs), with a focus on real-time image and point cloud processing. • Experience with sensor fusion, tracking, and object detection frameworks (YOLO, SSD, Mask R-CNN, etc.). • Skilled in Python/C++ and tools like OpenCV, PCL, TensorFlow, PyTorch, and CUDA. • Familiarity with ROS/ROS2, Carla, SUMO, or other AV simulation frameworks. • Proven ability in calibration and integration of perception sensors; understanding of HD Maps and environmental feature extraction. • Knowledge of SLAM and localization techniques is a strong plus. • Experience with testing and validation of perception systems in safety-critical environments. Nice to Have: • Experience with reinforcement learning or decision-making algorithms in unstructured environments. • Hands-on work with parallel processing (CUDA/OpenCL) and real-time optimization. • Familiarity with HD maps, OpenStreetMap integration, and high-resolution semantic mapping. Why You Should Join Us: • Play a central role in shaping how our vehicles see and interpret the world. • Join an ambitious, science-driven team that values deep collaboration and continuous learning. • Thrive in a flat hierarchy with fast decision-making and real ownership. • Work at the intersection of cutting-edge AI and real-world engineering in the heart of Berlin’s vibrant Kreuzberg.

Our client is revolutionizing autonomous driving with a unique approach rooted in cognitive neuroscience and cutting-edge German research. Their mission is to make intelligent, explainable decisions in complex traffic environments without relying on massive datasets. As one of the first companies in Germany to pursue level 4 certification for autonomous vehicles, they'refocused on safety, transparency, and scalability to shape the future of mobility—connecting people wherever they are. As a Geospatial Segmentation AI Engineer, you’ll develop the deep learning systems that enable our vehicles to perceive and understand the world through satellite, aerial, and sensor-based imagery. Responsibilities: • Design and implement AI models for semantic and instance segmentation using satellite, drone, and LiDAR imagery. • Develop preprocessing pipelines for geospatial image data using tools like GDAL, Rasterio, and GeoPandas. • Train, evaluate, and fine-tune CNN architectures (U-Net, Mask R-CNN, DeepLab, etc.) for high-resolution remote sensing tasks. • Integrate segmentation outputs into perception systems for urban/rural mapping, land use analysis, and road understanding. • Work with large-scale geospatial datasets (GeoTIFF, NetCDF, shapefiles, GeoJSON) and manage cloud-based geoprocessing workflows. • Build automated data pipelines for labeling, training, and validating geospatial models using tools such as CVAT, Labelbox, and QGIS. • Collaborate with perception, software, and sensor teams to align map data, real-time vision outputs, and spatial AI models. Requirements: • Strong experience with geospatial data processing and GIS tools (e.g., QGIS, GDAL, GeoPandas); understanding of CRS (e.g., WGS84, UTM). • Hands-on expertise in deep learning for image segmentation using frameworks like PyTorch, TensorFlow, or Keras. • Experience with satellite/aerial image analysis and handling raster/vector data formats. • Familiarity with CNN architectures like U-Net, HRNet, DeepLab, and object detection methods (YOLO, Mask R-CNN, etc.). • Proficient in Python and libraries such as OpenCV, scikit-image, Rasterio; experience with Jupyter, Docker, Git. • Knowledge of cloud platforms and services for geospatial processing (e.g., AWS SageMaker, Google Earth Engine) is a plus (negotiable). • Experience with GPU-based training, distributed learning, and handling largescale Earth observation data. Why You Should Join Us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. • Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district

Our client is revolutionizing autonomous driving with a unique approach rooted in cognitive neuroscience and cutting-edge German research. Their mission is to make intelligent, explainable decisions in complex traffic environments without relying on massive datasets. As one of the first companies in Germany to pursue level 4 certification for autonomous vehicles, they're focused on safety, transparency, and scalability to shape the future of mobility—connecting people wherever they are. As Head of Hardware, you will lead the development of the high-performance, safety critical systems that power their autonomous technology. Responsibilities: • Lead the design, development, and integration of embedded systems, PCBs, and specialized hardware (e.g., FPGAs, ASICs, SoCs) for autonomous vehicles. • Manage full hardware lifecycle including prototyping, testing (lab/field), quality assurance, and certification to automotive standards. • Develop and maintain sensor fusion hardware systems, integrating LiDAR, radar, cameras, GPS, and ultrasound into real-time perception pipelines. • Define and implement power management, signal processing, and thermal management strategies for reliable, efficient operation in-vehicle environments. • Oversee hardware-software integration across autonomy stacks, including ECUs, ADAS components, and V2X communication systems. • Guide a multidisciplinary hardware team using agile methodologies (Scrum, Kanban), ensuring timely delivery of hardware projects. • Collaborate with software, perception, and safety teams as well as suppliers and regulatory bodies to align on project goals, timelines, and compliance. Requirements: • Proven experience in automotive hardware development, including embedded systems (ARM, RISC-V), PCB design, and signal processing. • Strong knowledge of functional safety standards (ISO 26262), AEC-Q100, and design for reliability (DFR). • Familiarity with high-performance computing components (GPUs, TPUs, ASICs) and sensor hardware integration (LiDAR, radar, camera). • Experience with CAD tools (e.g., SolidWorks, Altium), PCB software (e.g., KiCad, Eagle), and simulation platforms (MATLAB/Simulink, PSpice). • Proficiency in communication protocols like CAN, Automotive Ethernet, and MOST. • Skilled in fault diagnosis, EMC/EMI testing, and reliability engineering for safetycritical environments. • Background in hardware prototyping, validation, and cross-functional project leadership. • Experience with cybersecurity and compliance standards for automotive electronics is a plus (negotiable). Why You Should Join Us: • Work in an intellectually stimulating and innovative environment where you can take full ownership of your projects. • Enjoy flat hierarchies, an open culture, and fast decision-making processes. • Collaborate with a skilled and dedicated team eager to share their knowledge and expertise. • Be part of a multinational workplace that values diversity and integrates different backgrounds and perspectives. • Work in the vibrant heart of Berlin, in the dynamic Kreuzberg district