Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world industrial ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world industrial ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
Applied Machine Learning Intern
Seattle, WA · On-site
Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world industrial ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
Applied Machine Learning Intern
Seattle, WA · On-site
Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world industrial ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
Applied Machine Learning Intern
Seattle, WA · On-site
Salary: Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
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Applied Machine Learning Intern
Seattle, WA · On-site
Salary: Applied Machine Learning Intern WaveWorks is building applied AI systems for real-world ... Process, clean, and structure large-scale audio/time-series datasets * Align data with ground truth ...
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Audio Machine Learning information
See Seattle, WA salary details
$33.6K - $48.3K
16% of jobs
$55K is the 25th percentile. Wages below this are outliers.
$48.3K - $63K
19% of jobs
$63K - $77.6K
13% of jobs
The median wage is $79.3K / yr.
$77.6K - $92.3K
14% of jobs
$92.3K - $107K
10% of jobs
$113.8K is the 75th percentile. Wages above this are outliers.
$107K - $121.7K
6% of jobs
$121.7K - $136.4K
4% of jobs
$136.4K - $151.1K
5% of jobs
$151.1K - $165.8K
4% of jobs
$165.8K - $180.5K
8% of jobs
$180.5K - $195.2K
0% of jobs
$33.6K
$96.1K
$195.2K
How much do audio machine learning jobs pay per year?
What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?
To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.
What are the typical daily responsibilities of someone working in Audio Machine Learning?
Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.
What is an Audio Machine Learning job?
An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.
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Full-time
Posted 14 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.