Paddy Hobson

AI Reinforcement Learning Specialist (Humanoid Robotics) Location: Pischelsdorf, Austria (Hybrid/Remote flexibility available) Company: Rosendahl Nextrom Employment Type: Full-TimeIMPORTANT: For this position we can only hire EU Citizens. We can support relocation for EU citizens. Our Client is a global technology leader in high-precision equipment for the battery, cable, wire, and fiber optic industries.  As they expand into AI and robotics, they are building a forward-thinking engineering team to develop humanoid labour as a service - a breakthrough offering for smart logistics, production, and beyond.We are seeking an AI Reinforcement Learning Specialist to train humanoid robots in both simulated and real-world environments. You will play a pivotal role in building the foundation of this new initiative, applying cutting-edge deep reinforcement learning to extend the intelligence and autonomy of robotic systems for industrial use. This is a startup-like environment within a well-established global engineering company - ideal for engineers who want autonomy, innovation, and impact. ResponsibilitiesDesign, train, and validate reinforcement learning models for humanoid robotic systems in simulated and physical environmentsIntegrate and optimize training using environments like Isaac SIM, MuJoCo, Unitree Sim, and OmniVerseDevelop robust, real-time systems with ROS 2, Linux, and C++/PythonCollaborate with mechanical, electrical, and AI teams to implement and test solutions on real hardwareUse tools such as GROOT, N1, and Cosmos to streamline deployment and visualizationResearch and apply state-of-the-art reinforcement learning algorithms for robotics (PPO, SAC, DDPG, etc.)Work toward a scalable ‘humanoid labor as a service’ platform adaptable to our industrial customer baseIdeal Candidate ProfileMSc or PhD in Robotics, Computer Science, AI, or related fieldProven experience applying reinforcement learning to robotic systemsHands-on expertise with simulators such as Isaac SIM, MuJoCo, and OmniVerseStrong skills in C++, Python, and working in Linux environmentsExperience with robotic middleware (ROS 2), sensors, actuators, and real-world integrationExcellent communication skills and a startup mindset—comfortable working in fast-moving, interdisciplinary teamsWhat We OfferCompetitive compensation package, tailored to candidate experience and market ratesFlexible working hours and hybrid/remote work possibilitiesOpportunity to work on a greenfield project with high visibility and executive supportCollaborative and innovation-driven environment, backed by Rosendahl Nextrom’s global reachAccess to internal and external training, conferences, and technical mentorshipVision & Mission This project is part of our long-term vision to deliver humanoid labor as a service—unlocking advanced robotics for industrial automation, logistics, and beyond. As this is a strategic new direction, you will have a voice in shaping not only the technology but also the business model behind it.

Senior Machine Learning Engineer (m/f/d) Join a mission-driven tech team applying cutting-edge AI to the recycling and waste management sector. They’re developing intelligent systems to optimize material detection, sorting, and process efficiency. Making industrial operations smarter and more sustainable. We're looking for a Senior Machine Learning Engineer with strong experience in computer vision and time series analysis to help design and deploy advanced models in production environments. What You’ll DoDevelop and deploy ML solutions for image and time-series data (e.g. object detection, anomaly detection, forecasting)Design scalable algorithms and integrate them into real-world systemsStay on top of the latest AI research and apply new technologies (e.g. Deep Learning, LLMs)Lead code reviews, mentor junior engineers, and promote development best practicesMonitor and continuously optimize models in productionWhat We’re Looking For4+ years of experience in CV (e.g. CNNs, YOLO) and time series (e.g. LSTM, Transformers)Strong Python/C++ skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, OpenCV)Proven record of building and deploying real-world ML applicationsSolid math and data analysis skillsFluent in English and German; strong communication and leadership abilitiesWhat We OfferA key role in shaping AI products in an innovative fieldFlat hierarchies, creative freedom, and an agile environmentA diverse, interdisciplinary team and flexible working optionsModern office space and participation in company success (e.g. VSOP)Salary Budget: €75 - 95k (Dependant on Experience)

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, we create autonomous systems that make logical, explainable decisions in complex road scenarios. Our 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 Reinforcement Learning Engineer, you'll be instrumental in advancing our unique decision-making framework based on cognitive neuroscience. Your expertise in inference-driven AI, probabilistic modelling, and goal-directed behaviour will help us develop explainable, adaptive systems for autonomous driving. Responsibilities: • Design and implement decision-making architectures based on Active Inference, Bayesian models, and reinforcement learning principles. • Develop generative models and inference-based systems to guide autonomous agents under uncertainty. • Integrate concepts from cognitive robotics, predictive coding, and goal directed behaviour into scalable autonomous driving modules. • Apply and extend the Free Energy Principle and planning-as-inference frameworks for real-world applications in perception and control. • Model and simulate agent-based, hierarchical inference systems to support adaptive, real-time decision-making. • Collaborate cross-functionally with neuroscience-inspired perception, planning, and systems teams to ensure coherence in cognitive modelling. • Analyse and validate behaviour of autonomous systems in both simulation and field test environments. Requirements: • Solid background in reinforcement learning, probabilistic inference, or computational neuroscience. • Experience with Active Inference, Bayesian inference, or hierarchical generative models. • Proficiency in Python (PyTorch, TensorFlow, or JAX), with the ability to implement and train complex inference systems. • Familiarity with decision-making under uncertainty, cognitive architectures, or embodied cognition frameworks. • Strong theoretical foundation in neuro-inspired AI, behavioural modelling, or theoretical neuroscience. • Experience integrating sensorimotor control, action selection, or adaptive control in real-time systems. • Background in robotics, autonomous agents, or AI planning systems is a strong plus. Note: Experience with interdisciplinary AI combining machine learning, neuroscience, and robotics is highly valued, but not strictly required. 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 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 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.

Searching for Applied Research Engineers to join a Zurich based company working on Humanoid Robotics.This company is working on the technology that allows an LLM promt to translate into Humanoid Robot manipulation. All of the founders hold PhDs in Robotics and Simulation with 15+ years experience working at a global technology leader, they already have a working demo and 3 humanoid robots on-site.The team has an abundance of experience in Robotics, Reinforcement learning, Dexterous Manipulation, Diffusion models and they're now searching for experts in VLM/LLMs.Requirements:PhD in Artificial intelligence (Ideally related to VLMs/LLMs)Practical experience in training and fine-tuning large language models (LLMs), as well as multimodal models like vision-language models (VLMs) and language-conditioned models such as Stable Diffusion or character animation systems.Experience in deploying these models in real-time in the cloud.Robotics experience is NOT needed for this position, we need someone who understands cutting edge generative models - there is already the experience in the team needed to translate this to the world of robotics.If you're interested in bringing your experience to the robotics domain with a fast growing and extremely well backed company then please apply!