Senior Edge AI Engineer: Audio ML

Edison Smart®

San Francisco (CA)

On-site

USD 180,000 - 200,000

Full time

2 days ago
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Benefits offered by this job

Medical, dental, and vision coverage
Life, AD&D, and disability insurance
HSA/FSA options
Employee Assistance Program

Job summary

Edison Smart seeks a Senior Software Engineer to develop and deploy machine learning models for audio applications running on edge devices. You will work across ML, software, and embedded systems to meet performance and customer requirements.

The role emphasizes building efficient edge solutions, collaborating with engineering teams, and contributing to a low-power AI hardware stack. On-site in the Bay Area with competitive compensation.

Qualifications

  • Bachelor's degree in CS, Engineering, or related field.
  • 3+ years developing and deploying ML models for audio applications.
  • Strong C++ and Python skills.
  • Experience with TensorFlow, PyTorch, or similar ML frameworks.
  • Experience working with large, complex codebases.
  • Experience with Embedded Linux.
  • Active security clearance or eligibility to obtain one.

Responsibilities

  • Develop, train, and optimize audio ML models for edge deployment.
  • Deploy models to resource-constrained embedded devices.
  • Work closely with engineering and customer teams to meet application requirements.
  • Develop and maintain software within complex codebases.
  • Optimize model performance for real-world edge AI applications.

Skills

C++
Python
Audio ML
Embedded Linux
Large codebases
Security clearance

Education

Bachelor's degree in Computer Science or Engineering

Tools

TensorFlow
PyTorch

Job description

Edison Smart seeks a Senior Software Engineer to develop and deploy machine learning models for audio applications running on edge devices. You will work across ML, software, and embedded systems to meet performance and customer requirements.

The role emphasizes building efficient edge solutions, collaborating with engineering teams, and contributing to a low-power AI hardware stack. On-site in the Bay Area with competitive compensation.

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