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Remote Audio Machine Learning Jobs (NOW HIRING)

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Allied

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and ... Remote Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Our machine learning engineering team is responsible for developing infrastructure and tooling to ...

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

SmarterDx

Senior Software Engineer, Machine Learning

$190/hr

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

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All JobsAudio Machine Learning 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 1, 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 99% Full Time, and 1% Part Time. Highlights an 37% Physical, 3% Hybrid, and 60% Remote job distribution, with an average salary of $84,456 per year, or $40.6 per hour.

Machine Learning Engineer, Personalization, Minesweeper

Spotify

Remote

$117.20K - $140.70K/yr

Full-time

Posted 24 days ago

Job description

Job Summary:
Spotify is a leading audio streaming platform that aims to enhance the listening experience through personalized recommendations. They are seeking a Machine Learning Engineer to join their Personalization team, focusing on developing AI and ML techniques to improve music, podcast, and audiobook recommendations for millions of users.
Responsibilities:
• Utilize in-house and 3rd party LLMs to solve language understanding problems
• Employ techniques such as fine-tuning and RAG to improve models
• Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
• Help drive optimization, testing, and tooling to improve quality of our content enrichment assets
• Collaborate with cross-functional teams of MLEs, data and backend engineers, and other stakeholders including tech research, data science, and product to develop new features and technologies
• Be a participant in our AI Foundation’s ML community and work collaboratively and efficiently within our existing platforms and systems Perform data analysis to establish baselines and inform product decisions
• Stay up-to-date on the latest machine learning algorithms and techniques
Qualifications:
Required:
• You have a strong background in machine learning, especially experience with Large Language Models
• You have professional experience in applied machine learning
• Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, with Python experience required) and cloud platforms (GCP or AWS)
• You have some hands-on experience implementing or prototyping machine learning systems at scale
• You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation
• You have experience and passion for fostering collaborative teams
• Experience with PyTorch, TensorFlow, and/or other scalable Machine learning frameworks. Experience with Ray or TFX is a plus
Preferred:
• Bonus if you have experience with architecting near real time pipelines
Company:
Spotify is a commercial music streaming service that provides restricted digital content from a range of record labels and artists. Founded in 2006, the company is headquartered in Stockholm, SWE, with a team of 5001-10000 employees. The company is currently Late Stage.

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