Job Description
Develop and enhance AI/ML models for Precision Music™ using advanced machine learning techniques and data analysis. Collaborate with cross-functional teams to integrate our proproetary AI-driven solutions that transform mental and physical well-being. Become a core team member evolving our VibeDNA™, Ai Music Brain™ and User Health Data models.
Introduction to Company:
Music Health is dedicated to transforming mental and physical well-being through AI-driven music-based experiences. Our core technology, Precision Music™, leverages our proprietary Ai MuVibeDNA to create personalized interventions that support better mental health.
Description of Role:
Key Responsibilities:
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Develop and improve machine learning models to enhance Precision Music™ capabilities.
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Utilize advanced AI/ML techniques to analyze music information retrieval, health data from wearables, and sentiment analysis.
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Collaborate with data scientists, engineers, and product teams to integrate AI-driven solutions into our products.
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Conduct research to stay updated on the latest AI/ML advancements and apply them to our technology.
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Optimize and maintain AI/ML pipelines for performance, scalability, and reliability.
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Implement and manage data preprocessing and feature engineering processes.
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Debug, troubleshoot, and resolve issues with AI/ML models and applications.
Qualifications:
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Senior level with at least 5 years of proven experience in AI/ML engineering.
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Demonstrable track record in developing and deploying machine learning models.
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Strong proficiency in Python, TensorFlow, PyTorch, and other relevant AI/ML frameworks.
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Experience with AWS Cloud services for deploying AI/ML models.
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Excellent problem-solving skills and a proactive approach to addressing challenges.
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Strong communication skills and ability to work in a team environment.
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Familiarity with music information retrieval, health data analysis, and sentiment analysis is a plus.
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Strong analytical skills and attention to detail.
Company Culture:
We have a policy of radical candor, no jerks, and plenty of empathy and collaboration.
