Computer Vision

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)

Job Title: MLOps EngineerWork Arrangement: RemoteLocation: Toronto, CanadaSalary: Up-to $125,000 CADMLOps Engineer – Real-Time AI SystemsWe're looking for an experienced MLOps Engineer to help deploy and scale cutting-edge ML models for real-time video and audio applications. You'll work alongside data scientists and engineers to build fast, reliable, and automated ML infrastructure.Key ResponsibilitiesBuild and manage ML pipelines for training, validation, and inference.Automate deployment of deep learning and generative AI models.Ensure model versioning, rollback, and reproducibility.Deploy models on AWS, GCP, or Azure using Docker and Kubernetes.Optimize real-time inference using TensorRT, ONNX Runtime, or PyTorch.Use GPUs, distributed systems, and parallel computing for performance.Create CI/CD workflows (GitHub Actions, Jenkins, ArgoCD) for ML.Automate model retraining, validation, and monitoring.Address data drift, latency, and compliance concerns.What You Bring3+ years in MLOps, DevOps, or model deployment roles.Strong Python and experience with ML frameworks (PyTorch, TensorFlow, ONNX).Proficiency with cloud platforms, Docker, and Kubernetes.Experience with ML tools like MLflow, Airflow, Kubeflow, or Argo.Knowledge of GPU acceleration (CUDA, TensorRT, DeepStream).Understanding of scalable, low-latency ML infrastructure.Nice to HaveExperience with Ray, Spark, or edge AI tools (Triton, TFLite, CoreML).Basic networking knowledge or CUDA programming skills.

Job Title: AI ResearcherWork Arrangement: HybridLocation: San JoseWe are seeking a talented Computer Vision AI Researcher with expertise in stable diffusion, diffusion models, GANs, NeRFs, and text-to-image/video synthesis.Key Responsibilities:Conduct pioneering research in computer vision, focusing on diffusion models and text-to-Image/videoDevelop advanced GAN architectures tailored for specific computer vision applications.Investigate NeRFs and related techniques to enhance 3D scene understanding.Drive advancements in text-to-image and text-to-video synthesis using deep learning methods.Collaborate closely with cross-functional teams to productise researchQualifications:Strong research background in stable diffusion, GANs, NeRFs, and text-to-image/video synthesis, evidenced by publications in top-tier conferences or journals.Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).Experience with large-scale data processing and model training.

Computer Vision Engineer – Hybrid Los Angeles – Up to $220k + Bonus + Equity Startup of 10+ engineers building next-stage real-time vision and sensing systems for defense and autonomy. Profitable and customer funded with no outside investment. Their platforms span digital terrain mapping, classical computer vision, and high performance signal processing, with hardware already deployed in the field. What You’ll Be DoingDesigning and implementing low-latency vision pipelines in C++ for mission-critical defense applications (e.g., region-of-interest tracking, camera calibration, sensor fusion).Collaborating closely with hardware teams to integrate cameras, IMUs, and other sensors on embedded platforms—pushing algorithms from prototype to production.Conducting field-testing (flight tests, desert range tuning) to validate and optimize real-world performance.Working on digital terrain modeling, object-tracking algorithms (drone-to-drone intercept, remote weapons platforms), and AR/display research.Writing reusable, well-documented code that ensures reliability under harsh conditions and tight real-time constraints.Must-Haves3+ years of professional experience developing C++ systems (preferably on Linux).Strong background in classical computer vision or signal processing (Kalman filters, ROI tracking, camera calibration, etc.).Comfortable working hands-on with sensors, cameras, and embedded hardware.Interest in field testing and tuning algorithms in live environments.U.S. Citizen or Green Card holder (required for defense-related work).Nice-to-HavesCUDA/OpenCL experience or other GPU-accelerated development.Prior work on SLAM or visual-inertial odometry for airborne or ground-robot platforms.Experience architecting software for long-range tracking (drones, aircraft, missiles).Familiarity with ROS, RTOS, or other robotics middleware.

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

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 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.