About the Company: Join us at our VC backed stealth-mode startup as we develop cutting-edge technology aimed at enhancing situational awareness and safety measures in diverse environments. We are a fast-growing team of innovators dedicated to making a significant impact through advanced technology solutions.
Role Overview: We are seeking a highly skilled Audio ML Engineer to join our engineering team. This role focuses on the development and implementation of machine learning models for audio analysis, with a particular emphasis on detecting and differentiating various sounds within specific environments. The successful candidate will be pivotal in enhancing our product’s ability to interpret and respond to a wide range of audio signals, including but not limited to gunshots, human speech, and mechanical and environmental noises.
Responsibilities:
Design and develop advanced machine learning algorithms for audio signal processing.
Implement real-time audio analysis systems capable of identifying and categorizing distinct sound types.
Collaborate with cross-functional teams to integrate audio detection models into hardware solutions.
Conduct rigorous testing and validation of models to ensure accuracy and reliability under various conditions.
Stay abreast of the latest developments in audio processing, machine learning, and related fields to continually improve our technology.
Travel to various states for acquiring training data, testing, and implementation.
Qualifications:
Proven experience in developing and implementing machine learning models for audio analysis.
Strong programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch.
Knowledge of digital signal processing techniques and acoustics.
Ability to work in a fast-paced, evolving environment while handling multiple priorities.
Excellent communication and collaboration skills.
What We Offer:
The opportunity to work on groundbreaking technology with potential life-saving applications.
A dynamic, innovative atmosphere with a focus on growth and professional development.
Hybrid work opportunities with flexible hours.
Note: Due to the confidential nature of our work, further details about the project will be shared during the latter stages of the interview process.
Employment type
Full-time
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