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Full Time Audio Machine Learning Jobs (NOW HIRING)

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Fundamentals of audio and speech signal processing. Pay Transparency Notice * Depending on your ...

Machine Learning Engineer - Edge

Lowell, MA · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Fundamentals of audio and speech signal processing. Pay Transparency Notice * Depending on your ...

Machine Learning Engineer - Edge

Dover, NH · On-site +1

$86K - $135K/yr

Machine Learning Engineer - Edge *Please consider before applying: This is a hybrid role, and ... Fundamentals of audio and speech signal processing. Pay Transparency Notice * Depending on your ...

They are seeking an experienced Machine Learning Engineer to own the full ML lifecycle, including ... audio, OCR, or deepfake classification. • Designing multilingual embedding systems with code ...

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

Machine Learning Engineer

New York, NY · On-site

$85K - $125K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Some travel is required, typically 5-25% * Full-time on-site work at the Kitware Office Preferred ...

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133.70K - $176.30K/yr

If you're excited about the future of video, audio, video content moderation, and more then you ... A degree in Computer Science, Machine Learning, or a related field, or equivalent professional ...

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Full Time Audio Machine Learning information

See salary details

$29.5K

$84.5K

$171.5K

How much do full time audio machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for full time audio machine learning in the United States is $84,456.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $113,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Audio Machine Learning Engineer, and why are they important?

To thrive as a Full Time Audio Machine Learning Engineer, you need a solid background in machine learning, digital signal processing, and proficiency in programming languages like Python or C++, often supported by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, and familiarity with audio analysis libraries and cloud computing platforms, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help you tackle complex audio data challenges and work effectively in multidisciplinary teams. These competencies are crucial for developing, optimizing, and deploying robust audio ML solutions that drive innovation in areas like speech recognition, music analysis, and sound classification.

What are some common challenges faced by professionals in full-time audio machine learning roles, and how can they be addressed?

Professionals in full-time audio machine learning roles often face challenges such as dealing with noisy or unbalanced datasets, managing high computational requirements for model training, and ensuring real-time processing capabilities. Overcoming these challenges typically involves applying advanced data augmentation techniques, leveraging specialized hardware (like GPUs), and optimizing models for efficiency. Collaboration with data engineers and domain experts is also crucial to refine data pipelines and validate model outputs. Staying updated with the latest research and open-source tools can further enhance problem-solving in this rapidly evolving field.

What is a Full Time Audio Machine Learning job?

A Full Time Audio Machine Learning job involves developing and applying machine learning algorithms to process and analyze audio data, such as music, speech, or environmental sounds. Professionals in this role work on tasks like audio classification, speech recognition, sound synthesis, and noise reduction. They often collaborate with data scientists, audio engineers, and software developers to build AI-driven applications for industries like entertainment, healthcare, and virtual assistants. This position typically requires strong programming skills, experience with machine learning frameworks, and a background in audio signal processing.

What is the difference between Full Time Audio Machine Learning vs Audio Data Scientist?

AspectFull Time Audio Machine LearningAudio Data Scientist
Required CredentialsDegree in Computer Science, Electrical Engineering, or related field; experience in machine learning and audio processingSimilar credentials; strong background in data science, statistics, and audio analysis
Work EnvironmentResearch labs, tech companies, startups focusing on audio applicationsData-driven teams, analytics departments, R&D units in tech or entertainment industries
Employer & Industry UsageTech firms developing speech recognition, audio enhancement, or sound classificationCompanies analyzing audio data for insights, product development, or quality control

Both roles require expertise in audio processing and machine learning, often sharing similar educational backgrounds. Full Time Audio Machine Learning specialists focus on developing models and algorithms, while Audio Data Scientists analyze audio data to extract insights. The roles are closely related and often overlap, but the former emphasizes model development, whereas the latter emphasizes data analysis and interpretation.

More about Full Time Audio Machine Learning jobs
What are the most commonly searched types of Audio Machine Learning jobs? The most popular types of Audio Machine Learning jobs are:
Infographic showing various Full Time Audio Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 17% Full Time, 79% Part Time, and 3% Temporary. Highlights an 68% Physical, 1% Hybrid, and 31% Remote job distribution, with an average salary of $84,456 per year, or $40.6 per hour.

Full-time

Posted 2 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.