Harvest Intelligence
ML & EMBEDDED VISION SYSTEMS ENGINEER
Join our team developing the hottest apps in the industrial mushroom farming sector. As an ML & Embedded Systems engineer focused on leading-edge computer vision & robotics applications, you will play a pivotal role in developing and applying cutting-edge technologies to optimize key aspects of our mushroom cultivation processes.
LOCATION
Cully, Switzerland
EMPLOYMENT TYPE
Permanent
What You’ll Do
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Participate in the development of AI models and algorithms to enhance mushroom cultivation efficiency, yield, and quality.
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Collaborate with cross-functional teams to design ML-powered solutions driving industrial machinery including robots
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Explore and implement advanced machine learning techniques for analyzing complex datasets related to growth conditions, environmental factors, and production outcomes.
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Optimise your code for running efficiently on edge computing platforms
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Develop predictive models for estimating mushroom growth patterns and optimizing harvesting strategies.
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Create and train AI models for real-time monitoring of cultivation parameters, enabling early detection of anomalies and potential issues.
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Collaborate with domain experts to integrate AI technologies into existing cultivation workflows.
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Experiment with emerging AI technologies and frameworks to drive continuous innovation in mushroom cultivation practices.
Who You are
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Ph.D. or Master's degree in Artificial Intelligence, Computer Science, Machine Learning, or a related field.
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Proven experience developing highly efficient code designed for embedded systems
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Strong programming skills in languages such as Python, along with experience using AI frameworks like TensorFlow, PyTorch, Keras, etc.
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Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
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Hands-on experience with Nvidia Jetson Orin processors is a plus
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Strong analytical and problem-solving abilities to tackle complex challenges
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Excellent communication skills to convey research findings to both technical and non-technical stakeholders.
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Ability to work collaboratively in interdisciplinary teams and manage research projects.