Are you ready to revolutionise the world with TEKEVER? 🚀🌍 At TEKEVER, we lead innovation in Europe as the European leader in unmanned technology, where cutting-edge advancements meet unparalleled innovation. 💻 Digital | 🛡️ Defence | 🔒 Security | 🛰️ Space We operate across four strategic areas, combining artificial intelligence, systems engineering, data science, and aerospace technology to tackle global challenges — from protecting people and critical infrastructure to exploring space. We offer a unique surveillance-as-a-service solution that delivers real-time intelligence, enhancing maritime safety and saving lives. Our products and services support strategic and operational decisions in the most demanding environments — whether at sea, on land, in space, or in cyberspace. 🌐 Become part of a dynamic, multidisciplinary, and mission-driven team that is transforming maritime surveillance and redefining global safety standards. At TEKEVER, our mission is to provide limitless support through mission-oriented game-changers, delivering the right information at the right time to empower critical decision-making. If you're passionate about technology and eager to shape the future — TEKEVER is the place for you. 👇🏻🎯 Mission: As a Computer Vision Lead, you will lead the Computer Vision Engineering team and take ownership of the Computer Vision technology strategy, roadmap and execution within TEKEVER’s wider Data & AI team. You will lead and mentor a team of experienced Computer Vision Engineers, drive innovation, and ensure delivery of robust, scalable, and high-impact Computer Vision algorithms, models and solutions. You will collaborate with cross-functional teams, guiding project planning, development priorities, and technical roadmaps. You will work closely together with the other teams within Data & AI (ML Engineering, Software Engineering, Data Science, Data Platform Engineering, Swarm AI Engineering and Product Management), as well as with related teams within the wider organisation (e.g. Ground Control Station, Onboard Systems, Autopilot). What will be your responsibilities: - Leadership: Lead, mentor and develop a team of Computer Vision Engineers, fostering a collaborative and innovative work environment. Showcase thought leadership in the field and inspire. - Strategy Development: Define and execute a compelling Vision, Strategy and Roadmap for the Computer Vision team, in line with wider business objectives. - Computer Vision Model, Algorithm and Solution Development: Lead and collaborate in the design, development and implementation of Computer Vision models, algorithms & solutions for image and video analysis, including object & event & change detection, recognition, segmentation and tracking. This includes leading, supporting and mentoring the Computer Vision Engineering team members in their activities, including model training & optimization, data pre-processing, collaboration with other expertise areas, computer vision model performance evaluation, deployment and documentation. Support the integration of our Computer Vision solutions within the wider portfolio of TEKEVER products (e.g. at the edge / UAV-onboard, Ground Control Station, Atlas). - Research and Innovation: Stay current with the latest advancements in computer vision and machine learning and apply new techniques to improve existing approaches and develop new solutions. - Project Management: Together with our Product Owners and Scrum Master, oversee the end-to-end lifecycle of Computer Vision projects and products, from ideation to deployment, ensuring timely delivery and high-quality outcomes, while reporting on progress in terms of milestones and timelines. - Recruitment: recruit new team members across Europe as the organization expands internationally. Profile and requirements: - Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field. A PhD is a plus. - Experience: 5+ years of experience in Computer Vision Engineering, including at least 2 years in a leadership or technical lead role. Proven track record managing a team and successfully delivering complex Computer Vision solutions. Strong analytical and problem-solving skills with a strategic mindset. - Leadership and soft skills: - Excellent team leadership and mentoring capabilities. - Collaborative mindset and ability to influence cross-functional teams. - Communication: Strong verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders. Able to translate complex technical concepts for diverse audiences. - Experience in defining robust Computer Vision strategies and roadmaps, managing multiple projects / products in parallel, while reporting on key milestones and timelines. - Adaptability: Ability to thrive in a fast-paced, dynamic environment. Technical Skills: - Allround experience covering classical to modern Computer Vision techniques. - Strong programming skills in Python and C++, including optimisation for real time performance. - Experience with relevant machine learning and deep learning models and frameworks such as YOLO. - Experience with frameworks and libraries such as OpenCV, TensorFlow, TensorRT, PyTorch, Keras and ONNX. - Experience with Feature Extraction & Matching Algorithms, Simultaneous Localization and Mapping (SLAM), Structure from Motion, Camera Pose Estimation, 2D/3D Object Detection, Instance Segmentation, Sensor Fusion, Point Clouds, Mensuration. - Experience with OpenGL and CUDA. - EO & IR image interpretation & processing (ideally including NIR, SWIR & radar). - Experience with imaging sensors, optics and interfaces, as well as data formats and video codecs, image and video processing techniques, video streaming, video stabilisation, metadata, camera interfacing, calibration. - Experience with ML tools, e.g. FiftyOne and ClearML. - Experience with experimentation platforms such as Jupyter Notebooks. - Knowledge of data pre-processing and augmentation techniques for computer vision tasks. - Experience in getting Machine Learning artefacts to production. - Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services, with focus on Google Cloud. - Basic knowledge of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc. - Experience with agile development. - Analytical Skills: Excellent analytical and problem-solving skills with the ability to design innovative solutions to complex problems. High attention to detail and a commitment to ensuring the accuracy and quality of work. What we have to offer you: - An excellent work environment and an opportunity to create a real impact in the world. - A truly high-tech, state-of-the-art engineering company with flat structure and no politics. - Working with the very latest technologies in Computer Vision, Data and AI, including Edge AI and Swarming - both within our software platforms and within our embedded on-board systems. - Flexible work arrangements. - Professional development opportunities. - Collaborative and inclusive work environment. - Salary compatible with the level of proven experience. Do you want to know more about us ? Visit our LinkedIn page at https://www.linkedin.com/company/tekever/

About Us Canibuild automates the residential construction industry’s design, approval, and sales processes, allowing clients to answer 'Can I build this on this plot of land?' instantly. As a fast-growing SaaS platform backed by Australia’s largest hedge fund, we serve clients across Australia, New Zealand, Canada, and the US. Job Overview We are looking for a Machine Learning Engineer with strong experience in Computer Vision and document understanding to help build AI-driven capabilities within our property technology platform. The role focuses on developing models that analyze visual and document-based data to extract structured information and support automated decision-making within our products. You will work closely with product and engineering teams to design, build, and deploy machine learning solutions that operate reliably in production environments. We are particularly interested in engineers who have taken machine learning systems from experimentation to production and are comfortable solving messy real-world data problems. Key Responsibilities - Design, develop, and deploy computer vision and machine learning models for analyzing visual and document-based data. - Build pipelines that convert unstructured visual inputs into structured and usable information. - Develop and evaluate models for tasks such as object detection, segmentation, document parsing, and image understanding. - Apply OCR and related techniques to extract meaningful information from complex documents and imagery. - Work with large datasets and build efficient training and evaluation pipelines. - Handle real-world visual datasets that may contain noise, inconsistencies, incomplete information, or varying formats. - Experiment with different approaches to solve challenging computer vision problems and evaluate tradeoffs between accuracy, performance, and complexity. - Collaborate with product and engineering teams to integrate machine learning models into scalable production systems. - Continuously improve model performance, accuracy, and robustness in real-world environments. - Stay up to date with the latest developments in AI and computer vision and apply relevant techniques where appropriate. - Actively leverage modern AI tools and frameworks to accelerate experimentation, development, and engineering workflows. Requirements - 5+ years of hands-on experience building and deploying machine learning models, particularly in Computer Vision or document understanding. - Strong proficiency in Python for machine learning and data processing. - Hands-on experience with modern ML frameworks such as PyTorch and libraries in the Hugging Face ecosystem. - Experience with computer vision tooling such as OpenCV. - Experience with common ML and data science libraries such as scikit-learn, NumPy, and Pandas. - Experience developing models for tasks such as segmentation, object detection, or document analysis. - Experience working with large image datasets and building training pipelines. - Solid understanding of model evaluation, data preprocessing, and performance optimization. - Strong problem-solving skills and ability to work in a fast-paced product environment. - Ability to collaborate effectively with cross-functional engineering and product teams. - The candidate should be based in Australia - Willing to work remotely full-time - Work schedule is Mon to Fri, 9:00 AM to 5:00 PM AEST Preferred Qualifications - Experience with TensorFlow or other deep learning frameworks. - Experience working with OCR pipelines or document analysis systems. - Experience deploying machine learning models in production environments. - Experience with containerized deployments such as Docker or Kubernetes. - Experience working with complex technical documents, diagrams, or structured visual data. - Familiarity with spatial or geometry-related data problems. - Experience with libraries such as Detectron2, MMDetection, or similar. - Familiarity with frameworks used to integrate modern AI models into applications (e.g., LangChain or similar tooling). - Contributions to open-source ML or computer vision projects are a plus. Additional Information - The problems we work on involve complex visual and document-based data, so we value engineers who enjoy tackling challenging technical problems and experimenting with different approaches to reach practical solutions. - Candidates are required to include link to relevant projects, GitHub repositories, research work, or examples of machine learning systems they have built. Benefits - Flexible remote work opportunities with career development opportunities - Engagement with a supportive and collaborative global team - Competitive market based salary

About Us Canibuild automates the residential construction industry’s design, approval, and sales processes, allowing clients to answer 'Can I build this on this plot of land?' instantly. As a fast-growing SaaS platform backed by Australia’s largest hedge fund, we serve clients across Australia, New Zealand, Canada, and the US. Job Overview We are looking for a Machine Learning Engineer with strong experience in Computer Vision and document understanding to help build AI-driven capabilities within our property technology platform. The role focuses on developing models that analyze visual and document-based data to extract structured information and support automated decision-making within our products. You will work closely with product and engineering teams to design, build, and deploy machine learning solutions that operate reliably in production environments. We are particularly interested in engineers who have taken machine learning systems from experimentation to production and are comfortable solving messy real-world data problems. Key Responsibilities - Design, develop, and deploy computer vision and machine learning models for analyzing visual and document-based data. - Build pipelines that convert unstructured visual inputs into structured and usable information. - Develop and evaluate models for tasks such as object detection, segmentation, document parsing, and image understanding. - Apply OCR and related techniques to extract meaningful information from complex documents and imagery. - Work with large datasets and build efficient training and evaluation pipelines. - Handle real-world visual datasets that may contain noise, inconsistencies, incomplete information, or varying formats. - Experiment with different approaches to solve challenging computer vision problems and evaluate tradeoffs between accuracy, performance, and complexity. - Collaborate with product and engineering teams to integrate machine learning models into scalable production systems. - Continuously improve model performance, accuracy, and robustness in real-world environments. - Stay up to date with the latest developments in AI and computer vision and apply relevant techniques where appropriate. - Actively leverage modern AI tools and frameworks to accelerate experimentation, development, and engineering workflows. Requirements - 5+ years of hands-on experience building and deploying machine learning models, particularly in Computer Vision or document understanding. - Strong proficiency in Python for machine learning and data processing. - Hands-on experience with modern ML frameworks such as PyTorch and libraries in the Hugging Face ecosystem. - Experience with computer vision tooling such as OpenCV. - Experience with common ML and data science libraries such as scikit-learn, NumPy, and Pandas. - Experience developing models for tasks such as segmentation, object detection, or document analysis. - Experience working with large image datasets and building training pipelines. - Solid understanding of model evaluation, data preprocessing, and performance optimization. - Strong problem-solving skills and ability to work in a fast-paced product environment. - Ability to collaborate effectively with cross-functional engineering and product teams. - The candidate should be based in India - Willing to work remotely full-time - Work schedule is Mon to Fri, 3:30am to 12:30pm IST Preferred Qualifications - Experience with TensorFlow or other deep learning frameworks. - Experience working with OCR pipelines or document analysis systems. - Experience deploying machine learning models in production environments. - Experience with containerized deployments such as Docker or Kubernetes. - Experience working with complex technical documents, diagrams, or structured visual data. - Familiarity with spatial or geometry-related data problems. - Experience with libraries such as Detectron2, MMDetection, or similar. - Familiarity with frameworks used to integrate modern AI models into applications (e.g., LangChain or similar tooling). - Contributions to open-source ML or computer vision projects are a plus. Additional Information - The problems we work on involve complex visual and document-based data, so we value engineers who enjoy tackling challenging technical problems and experimenting with different approaches to reach practical solutions. - Candidates are required to include links to relevant projects, GitHub repositories, research work, or examples of machine learning systems they have built. Benefits - Flexible remote work opportunities with career development opportunities - Engagement with a supportive and collaborative global team - Competitive market based salary

We are seeking reliable and detail-oriented Computer Operators to join our remote team. In this role, you will be responsible for monitoring computer systems, managing routine operations, and ensuring the smooth and efficient functioning of IT processes. You will play a key role in maintaining system performance, handling scheduled tasks, and responding to operational issues. Key Responsibilities System Monitoring & Operations * Monitor computer systems, servers, and applications to ensure optimal performance. * Execute scheduled jobs, batch processing, and system tasks. * Identify and respond to system alerts, errors, and performance issues. Data Management & Processing * Manage data input, processing, and output operations. * Verify data accuracy and integrity across systems. * Maintain logs and records of system activities and processes. Incident Handling & Support * Troubleshoot basic system and operational issues. * Escalate complex technical problems to appropriate IT teams. * Provide timely updates on system status and incident resolution. Documentation & Compliance * Maintain accurate documentation of processes, procedures, and system activities. * Ensure compliance with company policies, security standards, and operational guidelines. * Follow standard operating procedures (SOPs) for all tasks. Required Qualifications * High school diploma or equivalent (Associate's degree in IT or related field preferred) * 1–3 years of experience in computer operations, IT support, or data processing * Basic understanding of computer systems, networks, and operating systems * Familiarity with monitoring tools and office software * Strong attention to detail and organizational skills * Ability to follow instructions and work independently in a remote environment * Good communication and problem-solving skills Preferred Qualifications * Experience with batch processing systems or enterprise environments * Familiarity with Linux, Windows Server, or cloud-based systems * Basic scripting knowledge (e.g., Shell, PowerShell) is a plus * Experience working in 24/7 operations or shift-based environments Compensation & Benefits * Flexible remote work environment * Paid training and onboarding support * Opportunity to gain hands-on experience in IT operations * Career growth and advancement opportunities * Supportive and collaborative team culture Additional Requirements * Must be physically located within the United States * Must have a valid U.S. work permit (no sponsorship provided) * Ability to work flexible shifts, including nights, weekends, or holidays as needed * Reliable internet connection and a dedicated workspace