Key Responsibilities

• Camera and Illumination Selection:
• Evaluate and select appropriate cameras, lenses, and lighting techniques to meet application-specific requirements.
• Optimize imaging setups to ensure consistent and high-quality image acquisition.

Algorithm Development:

• Design, develop, and implement computer vision algorithms for defect detection, classification, and measurement.
• Employ deep learning and traditional vision techniques where applicable.

System Integration:

• Integrate vision systems into production machines, ensuring seamless operation.
• Collaborate with mechanical and electrical engineering teams to achieve optimal hardware-software integration.

Testing and Validation:

• Develop and execute test plans to validate system performance under real-world conditions.
• Iterate on solutions to improve robustness, speed, and accuracy.

Project Management:

• Lead technical discussions with clients to understand requirements and translate them into actionable plans.
• Manage project timelines and deliverables to ensure on-time delivery of high-quality solutions.

Innovation and Research:

• Stay updated on the latest advancements in computer vision, imaging technologies, and AI.
• Contribute to the continuous improvement of Evlos' vision systems and development pipeline.

Skills & Experience

• Bachelor’s or Master’s degree in computer science, Electrical Engineering, or a related field.
• At least 3 years of experience in machine vision, computer vision, or related fields.
• Proficiency in programming languages such as Python, C++, or MATLAB.
• Strong understanding of image processing, optics, and illumination techniques.
• Hands-on experience with machine vision libraries (e.g., OpenCV, Halcon, Cognex, or similar).
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
• Proven track record of developing and deploying vision solutions in industrial or manufacturing settings.

Preferred Skills

• Knowledge of industrial communication protocols (e.g., Modbus, Ethernet/IP).
• Experience with real-time vision systems and multi-camera setups.
• Familiarity with defect detection for parts such as plastic bottles, circuit boards, ceramics, or metallic plates.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.

You Can Apply If You:

• Have a Bachelor’s or Masters' degree in Computer Science, Electrical/Mechatronics Engineering, or a related field with a focus on computer vision or machine learning.
• Have extensive experience in developing and implementing computer vision algorithms.
• Are proficient in programming languages such as Python, C++, or Java.
• Have a strong background in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Have a solid understanding of image processing techniques and tools.
• Possess excellent problem-solving skills and the ability to work independently and in a team.