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Audio Machine Learning Intern Jobs (NOW HIRING)

Nanite Inc.

Machine Learning Engineer

Boston, MA

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The research intern will be in a fast-paced start-up environment playing a crucial technical role ...

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... The research intern will be in a fast-paced start-up environment playing a crucial technical role ...

Jane Street

Machine Learning Engineer

New York, NY

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... The interview process follows the same structure as our Software Engineering Intern interviews ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... The interview process follows the same structure as our Software Engineering Intern interviews ...

dbi

Alterations Intern

Cincinnati, OH

They will gain an understanding of the retail business by learning and completing skill level ... Gain experience and exposure to hand sewing and machine sewing projects. * Experience the art of ...

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Audio Machine Learning Intern information

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$25.5K

$42.6K

$88K

How much do audio machine learning intern jobs pay per year?

As of Jul 17, 2026, the average yearly pay for audio machine learning intern in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What does an Audio Machine Learning Intern do?

An Audio Machine Learning Intern assists in developing and improving machine learning models that process and analyze audio data. Their tasks may include data preprocessing, feature extraction, model training, and evaluation for applications like speech recognition, sound classification, or music analysis. Interns often collaborate with engineers and researchers to experiment with new algorithms and optimize audio-based AI systems. This role provides hands-on experience in both audio signal processing and machine learning techniques.

What types of projects can an Audio Machine Learning Intern expect to work on during their internship?

As an Audio Machine Learning Intern, you can expect to be involved in projects such as developing and fine-tuning audio classification models, working on speech recognition algorithms, or improving the accuracy of sound event detection systems. You may also assist with the collection and preprocessing of audio datasets, as well as support model evaluation and optimization. Collaboration with data scientists, audio engineers, and software developers is common, offering a hands-on learning environment and exposure to end-to-end machine learning workflows in the audio domain.

What are the key skills and qualifications needed to thrive as an Audio Machine Learning Intern, and why are they important?

To thrive as an Audio Machine Learning Intern, you need a solid background in signal processing, machine learning fundamentals, and programming skills, often supported by coursework or research in computer science or electrical engineering. Familiarity with Python, TensorFlow or PyTorch, and audio processing libraries like Librosa is typically required. Creativity, problem-solving abilities, and strong collaboration skills help you stand out in this role. These skills are crucial for developing innovative audio solutions, interpreting complex data, and working effectively within research or product teams.

What is the difference between Audio Machine Learning Intern vs Audio Data Analyst?

AspectAudio Machine Learning InternAudio Data Analyst
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fieldsDegree in Data Analysis, Statistics, or related fields; may have certifications in data tools
Work EnvironmentResearch labs, tech companies, or startups focusing on AI and audio techData-driven departments within media, entertainment, or tech companies
Employer & Industry UsageUsed in AI development, research projects, and product innovationUsed for analyzing audio data, improving user experience, and reporting

The Audio Machine Learning Intern focuses on developing models and algorithms for audio data, often in research or development settings. In contrast, the Audio Data Analyst primarily interprets audio data to generate insights and support decision-making. Both roles require familiarity with audio data, but the intern role emphasizes machine learning skills, while the analyst role centers on data analysis and reporting.

More about Audio Machine Learning Intern jobs
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Audio Machine Learning Intern jobs near you

Applied Machine Learning Intern

WaveWorks Technologies Inc

Seattle, WA

Full-time

Posted 22 days ago

Job description

Applied Machine Learning Intern

WaveWorks is building applied AI systems for real-world industrial environments. We are seeking a hands-on Applied Machine Learning Intern to work directly on live deployment data, develop modeling approaches, and take ownership of analysis for an active site.


RESPONSIBILITIES

  • Process, clean, and structure large-scale audio/time-series datasets
  • Align data with ground truth and validate data quality
  • Develop and evaluate modeling approaches for predictive maintenance
  • Design and run structured experiments, analyze results, and document findings
  • Improve data workflows and evaluation pipelines


REQUIRED QUALIFICATIONS

  • Pursuing a degree in Computer Science, Electrical Engineering, Data Science, or related field
  • Strong Python skills
  • Experience with ML frameworks (PyTorch, TensorFlow, or scikit-learn)
  • Comfortable working with real-world, noisy datasets
  • Strong analytical and documentation skills


PREFERRED QUALIFICATIONS

  • MS or PhD candidate in a relevant technical field
  • Experience with audio processing or time-series feature engineering
  • Familiarity with anomaly detection
  • Exposure to signal processing concepts (FFT, spectrograms, filtering)
  • Experience designing and evaluating structured ML experiments
  • Self-driven and comfortable operating in an early-stage environment



WaveWorks is committed to a friendly and welcoming working environment. WaveWorks does not discriminate based on race, gender, age, religious affiliation, or any other legally protected status.

WaveWorks is located in downtown Seattle, Washington.



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