Machine Learning Engineer - Edge

Machine Learning Engineer - Edge

The role is a hybrid position focused on developing edge AI/ML models for hearing and audio solutions.

• Design, train, fine‑tune, compress and deploy machine learning models that run efficiently on resource‑constrained edge devices.
• Collaborate with hardware engineers to integrate models into device architecture and optimize for low‑power environments.
• Maintain the software libraries, tools, and frameworks that support modern edge AI development.
• Collect, preprocess and analyze large, complex datasets to train, fine‑tune and validate models.
• Apply techniques such as model compression, quantization, pruning, and distillation to improve efficiency and runtime performance.
• Ensure models perform reliably in real‑world environments, meeting functional and non‑functional requirements.
• Identify, communicate and manage technical risks throughout the project lifecycle.
• Develop effective working relationships with cross‑functional teams and stakeholders.

• 2+ years of experience developing machine learning solutions, with a focus on audio and speech processing.
• Proficient in C, C++, and Python.
• Experience with edge‑focused machine learning frameworks such as Tensor Flow Lite, PyTorch, or comparable tools.
• Strong theoretical and practical understanding of ML architecture design, training, evaluation and deployment workflows.
• Knowledge of model compression, quantization, pruning and distillation for resource‑constrained edge devices.
• Experience with embedded systems and hardware platforms.
• Fundamental knowledge of audio and speech signal processing.

• Annual base salary range: $86,000‑$135,000, depending on location, role, skill set, and experience.
• Potential for discretionary bonus.
• Comprehensive benefits package including health insurance, 401(k) plan, paid time off and paid holidays.

All applicants will receive equal consideration for employment.

If you have a disability and need a reasonable accommodation to search for a job opening or to submit an online application, please e‑mail  We will respond only to emails specifically requesting accommodations.