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Remote Audio Machine Learning Jobs (NOW HIRING)

Apex Informatics

Machine Learning Engineer

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical ... audio and other unstructured data. • Collaborate with Product and Engineering teams to ensure ...

Alignerr

Machine Learning Engineer

Seattle, WA · Remote

Machine Learning Engineer (AI Data Trainer) About the Role What if your expertise in machine ... This is a fully remote, flexible contract role built for experienced ML and engineering ...

CloudDevs

Machine Learning Intern

Manhattan, NY · Remote

Join us to gain hands‐on experience in the exciting field of machine learning while working in a dynamic and collaborative remote environment. Responsibilities Assist in collecting, cleaning, and ...

Alignerr

Machine Learning Engineer

Denver, CO · Remote

$50 - $70/hr

Remote About the job At Alignerr, we partner with the world's leading AI research teams and labs to ... Machine Learning Engineer - AI Data Trainer Type : Hourly Contract Compensation : $50-$70 /hour ...

Spotify

Machine Learning Engineer

Spotify is a leading audio streaming service known for its innovative features like Blend and Discover Weekly. They are seeking a Machine Learning Engineer to join the Personalization team, focusing ...

GN Group

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 ...

ManTech International

Machine Learning Engineer

$128.80K - $214.50K/yr

General information Requisition # R67616 Locations USA-Remote Work Posting Date 05/19/2026 Security ... The Machine Learning Engineer will leverage their strong technical background and knowledge to ...

GN Hearing

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 ...

k1x

Machine Learning Engineer

Manhattan, NY · Remote

Fully Remote Position Preferred Locations: Midwest based: Indianapolis, IN or IL, Chicagoland Area ... As a Machine Learning Engineer, you will play a critical role in developing and implementing ...

GN Group

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 ...

GN Group

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 ...

10a Labs

Machine Learning Engineer

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 ...

Alignerr

Audio Engineer - Pro Tools

Miami, FL · Remote

Interest in AI-driven audio processing, sound analysis, or machine learning applications in music ... Fully remote and flexible - work from anywhere, on your own schedule * Clear ownership - know ...

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All JobsRemote Audio Machine Learning Jobs

Remote Audio Machine Learning information

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$29.5K

$84.5K

$171.5K

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

As of Jun 3, 2026, the average yearly pay for remote 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 Remote Audio Machine Learning Engineer, and why are they important?

To thrive as a Remote Audio Machine Learning Engineer, you need strong foundations in digital signal processing, machine learning algorithms, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, and audio processing libraries (e.g., LibROSA), as well as experience with cloud platforms, is highly valuable. Excellent problem-solving skills, self-motivation, and clear remote communication are essential soft skills for collaborating across distributed teams. These competencies enable the development of robust, innovative audio ML solutions while ensuring effective teamwork and project delivery in a remote setting.

How does a Remote Audio Machine Learning role typically collaborate with cross-functional teams, and what communication tools are commonly used?

In a Remote Audio Machine Learning position, collaboration with cross-functional teams such as software engineers, data scientists, and product managers is essential. Regular communication is maintained through tools like Slack, Zoom, and project management platforms such as Jira or Trello. Team members often participate in virtual stand-ups, sprint planning sessions, and code reviews to ensure alignment on project goals and timelines. Effective asynchronous communication and clear documentation are especially important in remote settings to keep everyone informed and foster a productive workflow.

What is a Remote Audio Machine Learning job?

A Remote Audio Machine Learning job involves using machine learning techniques to analyze, process, or generate audio data while working from a remote location. Professionals in this field develop algorithms for tasks such as speech recognition, music classification, noise reduction, or audio synthesis. They often work with large datasets, build and train models, and collaborate with teams online. These roles typically require skills in programming, signal processing, and experience with machine learning frameworks.

What is the difference between Remote Audio Machine Learning vs Remote Audio Engineer?

AspectRemote Audio Machine LearningRemote Audio Engineer
Required CredentialsBackground in machine learning, data science, or AI; often a degree in computer science or related fieldsAudio engineering, sound design, or music production degree or certification
Work EnvironmentPrimarily focused on developing algorithms, data analysis, and model training, often in a tech or research settingRecording, mixing, editing audio, often in studios or remote production setups
Employer & Industry UsageTech companies, research labs, AI startups working on audio recognition or enhancementMusic, film, broadcasting, and media production companies

Remote Audio Machine Learning specialists focus on developing algorithms to process and analyze audio data, while Remote Audio Engineers handle the practical aspects of recording and editing sound. Both roles may collaborate but serve different functions within the audio industry.

More about Remote Audio Machine Learning jobs
What cities are hiring for Remote Audio Machine Learning jobs? Cities with the most Remote Audio Machine Learning job openings:
What are the most commonly searched types of Audio Machine Learning jobs? The most popular types of Audio Machine Learning jobs are:
What states have the most Remote Audio Machine Learning jobs? States with the most job openings for Remote Audio Machine Learning jobs include:
What job categories do people searching Remote Audio Machine Learning jobs look for? The top searched job categories for Remote Audio Machine Learning jobs are:
Remote Audio Machine Learning jobs near you
Infographic showing various Remote Audio Machine Learning job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, 20% Part Time, and 5% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $84,456 per year, or $40.6 per hour.
Machine Learning Engineer

Machine Learning Engineer

Apex Informatics

Remote

Other

Posted 6 days ago

Job description

Applied Machine Learning Engineer | Music Software (Multiple Roles open)
Role: Applied Machine Learning Engineer (Mid - Senior Opportunity) Company: Splash
Employment Type: Contract (3 months +, potential for extension) Location: Remote
We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production-ready API code). In this role, you'll leverage off-the-shelf tools and custom-built ML models to solve challenges in music product development and improve manual music processes. This position is ideal for engineers with demonstrable experience building functional, production-ready models and who are passionate about user experience and Product.
Key Responsibilities:
• Design and implement ML algorithms to enhance music creation tools and solve various user problems in line with product goals.
• Identify and implement off-the-shelf ML and AI tools to solve practical problems efficiently.
• Understand the requirements of running models in production, including domain shift testing, QA, A/B testing and so on.
• Maintain production-ready code with considerations for how solutions fit the product and enhance the user experience.
• Build scalable, maintainable data pipelines to handle audio and other unstructured data.
• Collaborate with Product and Engineering teams to ensure seamless integration of ML solutions into production systems.
• Evaluate, deploy, and fine-tune pre-trained models for tasks like audio analysis, melody generation, and process automation.
• Uphold ethical AI practices, ensuring fairness and responsible AI use in music-related applications.
What You Bring
• Proven software development experience, ideally in Python (other languages a plus).
• Experience implementing and deploying ML models, using PyTorch framework.
• Familiarity with AWS cloud environment for deploying and scaling ML solutions.
• Ability to preprocess and model unstructured data, especially audio.
• A strong focus on applied problem-solving, with a practical approach to integrating existing tools and systems.
• A good understanding of music, production, or audio technology processes (or a strong interest in music)
• Familiarity with GenAI architectures like transformers, LLMs, or diffusion models.
• Proactive nature, ability to creatively solve problems you face and bring new ideas to the team.
• Clear and effective communication with technical and non-technical stakeholders.
• Ability to work independently and remotely while collaborating closely with cross-functional teams.

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