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Remote Audio Machine Learning Jobs (NOW HIRING)

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Jobgether

$94K - $124K/yr

The role combines deep backend and ML engineering with realtime audio, inference infrastructure ... Flexible working hours and remote work options . * Health, dental, and vision benefits for ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Perform advanced exploratory data analysis on large-scale sensory datasets (image, audio, radar ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

Perform advanced exploratory data analysis on large-scale sensory datasets (image, audio, radar ... Proficiency in Unix-based environments (Linux, macOS) including working with remote servers and ...

Weekday AI

Machine Learning & NLP Expert

$80 - $110/hr

This is a part-time, fully remote opportunity requiring approximately 20 hours per week . Requirements Key Responsibilities * Design challenging, real-world machine learning and natural language ...

Shure

Audio DSP Engineering Intern

Niles, IL · On-site +1

$16.75 - $21.75/hr

We offer internships with a variety of work arrangements from onsite interns to fully remote in US ... Deliver digital signal processing and Machine Learning features into a variety of intelligent ...

Shure

Audio DSP Engineering Intern

Niles, IL · On-site +1

$16.75 - $21.75/hr

We offer internships with a variety of work arrangements from onsite interns to fully remote in US ... Deliver digital signal processing and Machine Learning features into a variety of intelligent ...

Shure

Audio DSP Engineering Intern

Niles, IL · On-site +1

$16.75 - $21.75/hr

We offer internships with a variety of work arrangements from onsite interns to fully remote in US ... Deliver digital signal processing and Machine Learning features into a variety of intelligent ...

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Remote Audio Machine Learning information

See salary details

$29.5K

$84.5K

$171.5K

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

As of Sep 15, 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 is a remote audio machine learning?

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 are the key skills and qualifications needed to thrive as a remote audio machine learning engineer?

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 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:

What other helpful pages are available for Remote Audio Machine Learning?

Other pages related to Remote Audio Machine Learning:

Remote Audio Machine Learning jobs near you
Infographic showing various Remote Audio Machine Learning job openings in the United States as of September 2026, with employment types broken down into 100% Contract. Highlights an 100% Remote job distribution, with an average salary of $84,456 per year, or $40.6 per hour.

Instructor, AI/Machine Learning - NLP & Audio Analytics, Simplilearn (Part time

Remote

Fullstack Academy
Colleges, Universities, and Professional Schools • 51 - 200 employees
Learn more about Fullstack Academyexternal

$50 - $55/hr

Full-time, Part-time

Re-posted 17 days ago

Job description

About: Simplilearn
Simplilearn is the world's #1 online Bootcamp provider, enabling learners around the globe with rigorous and highly specialized training offered in partnership with world-renowned universities and leading corporations. We focus on emerging technologies and skills, such as data science, cloud computing, programming, and more - that are transforming the global economy. Our training is hands-on and immersive, including live virtual classes, integrated labs and projects, 24x7 support, and a collaborative learning environment. Over two million professionals and 2000 corporate training organizations across 150 countries have harnessed our award-winning programs to achieve their career and business goals.
Simplilearn has collaborated with Fullstack Academy to leverage its widespread footprint in the US region and partnerships with Top US universities to grow internationally.
Requirements
Job Summary
We are hiring experienced NLP & Audio Analytics Trainers to deliver live online training sessions with hands-on labs and real-world projects for working professionals.
Key Responsibilities
  • Conduct live, instructor-led online classes
  • Deliver coding demos, assisted practices, and projects
  • Address learner queries and ensure engagement
Required Skills
Natural Language Processing
  • NLP fundamentals, tools, and libraries (NLTK)
  • Text preprocessing, feature engineering, and visualization
  • Text vectorization: One-Hot, BoW, TF-IDF
  • Sentiment analysis using Naive Bayes
  • Word embeddings: Word2Vec, GloVe
  • Machine Translation and document search (TF-IDF, BM25)
  • Sequence models (RNNs) and challenges
  • Attention models, Transformers, BERT, GPT
Audio Analytics & Speech
  • Audio processing using Python (Librosa, PyDub)
  • Audio visualization and feature extraction
  • Digital Signal Processing and MFCCs
  • Deep Learning for speech recognition
  • Transfer learning for speech models
  • Audio synthesis and music generation using GANs

Working Hours -
The total weekly part-time commitment is expected to be 8-12 hours.
Weekday - 06:30 PM CST - 09:30 PM CST
Weekend - 09:00 AM CST - 12:00 PM CST
Class Timings -
For Weekend sessions, 6-8 hrs of delivery
- For Weekday sessions, 9-12 hrs of delivery
- 1 prep hour/session for the first cohort and 0.5 prep hour per session for the future cohorts
- If content revamped, prep can be at 1 hour/session for the first batch and 0.5 hour per session for the future batches
***Feedback communication/General connects Minutes/hours are not billable
***Prep hour can be billed only for the actual scheduled teaching hours(Induction sessions excluded)
Qualifications
  • 10+ years of hands-on experience in NLP and/or Audio Analytics
  • Strong Python and ML/DL skills
  • Prior online/classroom training experience

Benefits
Compensation:
The expected compensation for this role for candidates from United States is $50 -$55 per hour for candidates who fulfill the qualifications for the role. Candidates whose qualifications are above those listed are encouraged to apply as well. All final offers to candidates will be based on that candidate's unique experience and skillset, and not all candidates will qualify for the top of the salary range.
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