Computer Vision Engineer
hace 3 semanas
We are seeking a highly skilled Computer Vision Engineer to join our Artificial Intelligence and Computer Vision (AICV) Competence Centre at Deimos Space. As a key member of our team, you will play a crucial role in researching, developing, deploying, and scaling our Machine Learning and Computer Vision portfolio for onboard processing applications in Space.
Key Responsibilities- Research and Development: Design, implement, and deploy Computer Vision and/or Machine Learning algorithms that address specific challenges and opportunities related to onboard processing in Space.
- Collaboration and Teamwork: Collaborate with team members and clients across Europe to understand project requirements, objectives, and constraints.
- Infrastructure Development: Design, implement, and maintain industry-standard infrastructure for new and existing Computer Vision products.
- Data Analysis: Process and analyze datasets to extract meaningful insights and features.
To be successful in this role, you will need:
- Strong Foundation in Computer Vision: A strong foundation in image processing and computer vision techniques, such as filtering, edge detection, and segmentation, with relevant technical project experience.
- Programming Skills: Proficiency in programming languages and frameworks such as Python, C++, MATLAB, OpenCV, scikit-image, and dlib.
- Algorithms and Data Structures: Proficiency in algorithms and data structures.
- Software Development Life Cycle: Knowledge of software development life cycle and agile methodologies.
- Machine Learning: A basic understanding of Machine Learning.
The following skills are highly desirable:
- Machine Learning Frameworks: Good understanding of Machine Learning concepts and frameworks such as TensorFlow, PyTorch, and Keras.
- Aerospace Experience: Experience working on aerospace-related projects.
- MLOps and CI/CD: Experience deploying MLOps solutions and working within CI/CD frameworks.
- Cloud Infrastructure: Experience with Linux systems and cloud infrastructure (AWS, Azure, etc.).
- Embedded ML: Experience developing embedded ML applications (C++, CUDA, TensorRT).
Good level of English, spoken and written. Any other languages would be considered an asset.
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