Aktuelle Jobs im Zusammenhang mit Lead Engineer in Audio Machine Learning - Berlin, Berlin - 60 Degrees Ltd
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Machine Learning Engineer
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Machine Learning Engineer
vor 1 Monat
Berlin, Berlin, Deutschland Noah Labs VollzeitAbout Noah LabsWe are a pioneering healthcare technology company dedicated to developing innovative software solutions that address cardiovascular diseases. Our mission is to empower healthcare professionals and patients with cutting-edge analytics and insights.Job SummaryWe are seeking a highly skilled Lead AI/Machine Learning Engineer to join our team. As...
Lead Engineer in Audio Machine Learning
vor 2 Monaten
60 Degrees Ltd, a pioneer in enhancing auditory experiences and safeguarding hearing wellness, is on the lookout for a Lead Engineer in Audio Machine Learning to become a vital part of their innovative team. The selected individual will be instrumental in crafting and refining real-time audio algorithms and machine learning methodologies, driving the evolution of state-of-the-art personalized audio solutions.
Our organization has pioneered a unique, biologically-inspired audio processing technology designed to assess auditory capabilities, thereby customizing the listening experience and mitigating the risk of hearing impairment.
To assist us in delivering exceptional auditory technology to a broader audience, we are eager to welcome a Lead Engineer in Audio Machine Learning.
KEY RESPONSIBILITIES
As our Lead Engineer in Audio Machine Learning, you will be responsible for...
- Establishing the foundation for a comprehensive Machine Learning Lifecycle with a focus on:
- Machine Learning Engineering: Modify, train, and enhance cutting-edge models for real-time audio applications
- MLOps: Organize datasets and configure training frameworks
- Grasping the requirements for embedded systems and perceptually significant elements, including perceptual loss functions and metrics
- Refining models for various product applications, employing techniques such as pruning and quantization
- Preparing models for deployment in collaboration with integration engineers
QUALIFICATIONS AND SKILLS
- Extensive experience with real-time audio models
- Familiarity with tinyML tools and methodologies
- Expertise in PyTorch or TensorFlow
- Experience with TensorFlow Lite Micro Runtime
- Proficient in developing high-quality audio datasets
- Current knowledge of research and industry advancements
- Strong self-motivation and accountability, with a proactive approach to identifying challenges, proposing solutions, and effectively collaborating with colleagues to meet both team and organizational objectives
- Excellent communication skills to articulate complex concepts through both written and verbal means
