Computer Vision Engineer

As a Computer Vision Engineer at Rapsodo, you will be responsible for developing and implementing advanced computer vision algorithms, such as 3D vision and image classification. You will also conduct research to apply advanced techniques in statistics and optimization that enhance our cutting-edge image processing solutions, all while ensuring seamless integration with existing systems.

To qualify for the Computer Vision Engineer position at Rapsodo, candidates should have a Master's or PhD in Computer Science or a related field with a focus on Computer Vision and image processing. Additionally, applicants should possess 3-5 years of relevant experience, showcasing strong expertise in 3D vision, image classification, and proficiency with OpenCV and programming languages like C/C++ and Python.

At Rapsodo, collaboration is key! As a Computer Vision Engineer, you'll work closely with cross-functional teams, including data scientists and UI/UX designers, to implement and refine vision-based solutions. This teamwork ensures that we deliver the best products possible, merging different expertise to create state-of-the-art solutions for athletes.

Computer Vision Engineers at Rapsodo utilize a variety of technologies, including OpenCV for vision-based application development, linear algebra techniques for optimization, and advanced programming skills in C/C++ and Python. You’ll also design and maintain sophisticated software architectures and APIs that are fundamental in our product development.

At Rapsodo, career growth is not just a possibility – it’s encouraged! As you contribute to innovative projects as a Computer Vision Engineer, there will be ample opportunities for professional development, networking with experts, and furthering your skills in the rapidly evolving field of sports technology. We value team players who strive for excellence!

When answering this question, be specific about the projects you’ve worked on, the challenges faced, and how you utilized OpenCV to achieve your objectives. Highlight the libraries and functionalities within OpenCV you are most proficient in, and how they contributed to your success in implementing vision-based applications.

Discuss your method for optimizing algorithms, including understanding the trade-offs between accuracy and performance. Mention specific techniques or strategies you’ve implemented in previous projects, and be ready to provide examples of how these optimizations improved the efficiency of your algorithms.

Provide insight into any relevant projects involving 3D vision, explaining the technologies and methods used. It's essential to share your understanding of concepts such as depth perception, stereo vision, or 3D reconstruction, highlighting your role in bringing those projects to fruition.

This is your chance to showcase your problem-solving skills. Outline the problem, the steps you took to analyze and address it, and the outcome. Emphasize your analytical thinking, creativity, and how you collaborated with others, if applicable, to arrive at a solution.

When responding, mention the programming languages you are proficient in, such as C/C++ and Python. Discuss the strengths of each regarding computer vision tasks and share any personal preferences based on your experiences, explaining how these languages helped you accomplish your project goals.

Show your commitment to continuous learning by mentioning specific resources, websites, publications, conferences, or communities you engage with to remain current in the field. Discuss how this ongoing learning has positively impacted your work or inspired new techniques you’ve implemented.

Here, lay out the significance of camera calibration in ensuring accurate image interpretation. Discuss how calibration can affect different parameters like lens distortion and perspective, and relate it to real-world applications within your experience, showcasing your understanding of the underlying math.

Explain how you actively engage with other team members, from sharing ideas to managing conflicts. Highlight your communication skills, adaptability, and examples of successful collaborative projects, demonstrating your ability to work in a team-oriented environment like Rapsodo.

Discuss how machine learning algorithms can be leveraged to improve image classification and object detection. Share specific instances where you’ve applied machine learning techniques in your projects, illustrating the benefits they brought to the overall functionality of vision applications within your experience.

In your response, provide examples of any APIs you’ve designed or maintained, particularly in the context of computer vision. Discuss your understanding of key design principles, the importance of intuitive interfaces, and how your work contributed to the smooth integration of technologies in your projects.