Audio ML Research Intern: Deep Learning & DSP

Jobtailor

Niles (IL)

On-site

USD 90,000 - 140,000

Full time

38 hours ago
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Job summary

Jobtailor is seeking a highly skilled ML researcher to develop and optimize audio-focused machine learning solutions. The role involves dataset curation, designing and evaluating deep learning models for audio tasks, and deploying across multiple platforms.

You will collaborate with research and engineering teams to share insights and advance audio intelligence initiatives. You will apply modern ML engineering practices, document findings, and communicate results effectively.

Qualifications

  • Pursuing a PhD or advanced Master’s in a quantitative field (EE, CS, math, stats, physics, data science, ML)
  • Demonstrated research or project experience in ML, DL, or AI
  • Experience applying ML to audio, speech, DSP, multimedia or related domains
  • Proficiency with ML frameworks such as PyTorch, TensorFlow, or JAX
  • Strong Python programming and scientific computing skills
  • Ability to independently investigate complex technical challenges and prototype solutions
  • Strong written and verbal communication skills
  • Experience with audio signal processing, acoustics, speech processing, or music information retrieval
  • Familiarity with MLOps: experiment tracking, versioning, CI/CD, scalable training
  • Experience deploying ML models to embedded, edge, mobile, cloud, or realtime systems
  • Experience with full-stack development and cloud technologies
  • US work authorization for full-time employment; no visa sponsorship
  • Shure will not sponsor applicants for work visas

Responsibilities

  • Conduct research and develop machine learning solutions for audio problems
  • Collect, create, and curate datasets for model development and evaluation
  • Design, train, and evaluate deep learning models for audio applications (single- and multi-channel processing, speech/music enhancement, audio classification)
  • Investigate and implement state-of-the-art approaches
  • Optimize and adapt models for deployment across hardware and software platforms
  • Apply modern ML engineering practices (shared codebases, reusable toolkits, experiment tracking, reproducible workflows)
  • Document research findings and recommendations using collaboration tools
  • Present technical results and insights to research and engineering teams

Skills

Machine Learning
Deep Learning
Audio Processing
Python Proficiency
MLOps
Experiment Tracking
Data Curation
Prototyping
Signal Processing
Communication Skills
Independent Problem Solving

Education

PhD or advanced Master’s in a quantitative field

Tools

PyTorch
TensorFlow
JAX
CI/CD Tools
Cloud Technologies
Scientific Computing Tools

Job description

Jobtailor is seeking a highly skilled ML researcher to develop and optimize audio-focused machine learning solutions. The role involves dataset curation, designing and evaluating deep learning models for audio tasks, and deploying across multiple platforms.

You will collaborate with research and engineering teams to share insights and advance audio intelligence initiatives. You will apply modern ML engineering practices, document findings, and communicate results effectively.

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