Computer Vision Engineer

At Equashield, we are pioneers in hazardous drug safety, revolutionizing the way healthcare providers handle and administer medication with best-in-class CSTD and pharmacy automation through robotics.
We are seeking a talented Computer Vision Engineer to join our Automation division and lead the development of computer vision and machine learning systems that give our robots the ability to see and operate with precision in real-world pharmacy environments. Your work will directly impact patient safety by enabling accurate, intelligent, and reliable medical robotics.
What You'll Do
Design and develop computer vision pipelines for object detection, recognition, classification, and anomaly detection from live and recorded camera feeds.
Integrate perception algorithms with robotic control systems to improve automation accuracy and real-time responsiveness.
Develop and optimize ML models for deployment in embedded and real-time robotic environments.
Collaborate closely with software, hardware, QA, and product teams to embed vision capabilities into end-to-end automation workflows.
Build and maintain MLOps work

דרישות:

B.A./B.Sc. in Computer Science, Electrical Engineering, or a related technical field.
3–6 years of hands-on experience in computer vision and/or machine learning engineering.
Strong Python development skills — clean, modular, production-ready code.
Deep knowledge of computer vision frameworks and tools (OpenCV, Pillow, torchvision, or similar).
Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Solid understanding of ML fundamentals: supervised/unsupervised learning, model evaluation, validation metrics.
Experience integrating vision or ML models into real-time systems or backend services via REST APIs.
Ability to work both independently and collaboratively within a multidisciplinary team.
A curious, rigorous mindset with a passion for applying data-driven solutions to real-world challenges.

Nice to Have
Experience deploying ML models to production environments (Docker, containers, REST services, edge devices).
Background in real-time image processing, 3D vision, or depth sensing (stereo cameras, structured light, time-of-flight).
Experience with cloud ML pla