Company Description

Algorized is a VC-funded Silicon Valley deep-tech company with Swiss roots building edge-AI models that give robots real-time human awareness using existing wireless sensors - enabling safer human-machine co-presence. 

As we continue to scale rapidly, we are looking for a Data Scientist to design, build, and maintain scalable machine learning algorithms to create and deploy the models that process data from sensors, radar, and cameras. This role will be critical in ensuring high performance, real-time accuracy, and seamless ML model performance on the edge. 

Responsibilities

• Design, improve and implement complex machine learning models and algorithms processing raw radar sensor data and other sensor data to address customer business needs 

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• Manage the ML data pipeline, including data collection, extraction, validation, and preprocessing

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• Format, restructure, or validate datasets to ensure high data quality, and readiness for analysis 

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• Develop robust data preprocessing methods to enhance model accuracy and efficiency 

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• Analyze extensive datasets to identify trends and patterns and interpret them 

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• Build the foundation for highly scalable data collection and analytics 

Qualifications

• MSc/PhD in Data Science, Mathematics, Computer Science or related field

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• Experienced in algorithm design and optimization 

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• 3+ years hands-on experience in a similar position (1+ for candidates with PhD) 

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• Expertise in sensor fusion, edge AI, or embedded ML models for real-time applications ​​​

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• Good coding skills in Python, familiarity with PyTorch, scikit-learn and other Python ML libraries 

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• Experience with time-series data, sensor data pipelines, or stream processing frameworks 

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• Good understanding of ML model deployments 

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• Excellent teamwork & communication skills, with a passion for innovation and solving complex challenges 

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• Genuine interest in solving challenging people-sensing problems from start to finish 

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• Willingness to travel domestically and internationally for development and on-site customer support