Paddy Hobson

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 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.