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 workflows including model versioning, evaluation, and continuous validation.
• Document models, experiments, and validation processes in compliance with regulatory and audit requirements.
• Contribute to architecture decisions, code quality standards, and engineering best practices across the team.

What You Bring

• 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 platforms (AWS SageMaker, Azure ML, Google Vertex AI).
• Knowledge of robotics systems, control loops, or hardware–software integration.
• Familiarity with regulated or medical device software environments (ISO 13485, IEC 62304).
• Experience working with agentic AI systems and understanding model behavior in automated pipelines.

Why Equashield?

• Work on mission-driven projects that directly improve patient safety and healthcare outcomes.
• Apply computer vision and machine learning in a real-world medical automation environment with genuine clinical impact.
• Collaborate in a multidisciplinary team combining robotics, embedded systems, software, and AI.
• Grow with a fast-scaling global company at the forefront of pharmacy automation technology.
• Take ownership of high-visibility work that shapes the intelligence layer of next-generation medical robots.