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Audio Machine Learning Jobs in Los Angeles, CA (NOW HIRING)

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA

$140K - $170K/yr

... speech/audio and image/video. The Sr Engineer, AI & ML will also closely work with our software ... Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

... speech/audio and image/video. The Sr Engineer, AI & ML will also closely work with our software ... Develop new advanced algorithms using, machine learning techniques, deep learning models, digital ...

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All JobsAudio Machine Learning JobsAudio Machine Learning Jobs in Los Angeles, CA

Audio Machine Learning information

See Los Angeles, CA salary details

$31.8K

$91K

$184.8K

How much do audio machine learning jobs pay per year?

As of Aug 25, 2026, the average yearly pay for audio machine learning in Los Angeles, CA is $91,002.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,900.00 and $121,800.00 per year, depending on experience, location, and employer.

What is an audio machine learning?

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.

What does an audio machine learning do?

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 are the key skills and qualifications needed to thrive in audio machine learning?

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 most commonly searched types of Audio Machine Learning jobs in Los Angeles, CA?

The most popular types of Audio Machine Learning jobs in Los Angeles, CA are:

What are popular job titles related to Audio Machine Learning jobs in Los Angeles, CA?

For Audio Machine Learning jobs in Los Angeles, CA, the most frequently searched job titles are:

What job categories do people searching Audio Machine Learning jobs in Los Angeles, CA look for?

The top searched job categories for Audio Machine Learning jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Audio Machine Learning jobs?

Cities near Los Angeles, CA with the most Audio Machine Learning job openings:

Audio Machine Learning jobs near you
Infographic showing various Audio Machine Learning job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 21% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $91,002 per year, or $43.8 per hour.

Machine Learning Scientist

Irvine, CA • On-site

Intratek Computer, Inc.
IT Services • 201 - 500 employees
Learn more about Intratek Computer, Inc.external

$100 - $130/hr

Other

Medical, PTO

Posted 7 days ago

Job description

Machine Learning Scientist (Direct Hire – Onsite in Irvine, CA)

Location: Irvine, CA (Onsite / Hybrid, Monday–Friday, First Shift) or Out of area candidates that fit the qualifications may be considered, for relocation or remote employment with periodic travel to Irvine, CA office.
Employment Type: Direct Hire
Compensation: DOE (Depending on Experience)
Start Date: ASAP
Benefits: Medical, Paid Vacation, Paid Holidays, Stock Options

We are currently recruiting for a Machine Learning Scientist for a direct-hire role with one of our clients, a technology company based in Irvine, CA. This is not a contract role.

Position Overview

The Machine Learning Scientist will join a specialized ML team to design, develop, and test advanced deep learning algorithms focused on steganography and media watermarking across digital media formats (images, video, audio, etc.). You will also work closely with engineering teams to deploy these models into production environments, including mobile and cloud platforms.

Key Responsibilities
  • Research, design, and implement state-of-the-art deep learning–based steganography algorithms.
  • Collaborate with engineering teams to integrate and deploy ML models to customer-facing platforms.
  • Benchmark and evaluate new models against legacy approaches to ensure quality and accuracy.
  • Prepare clear technical documentation, reports, and presentations to communicate findings to internal teams.
Required Qualifications
  • Expert-level experience with PyTorch and training/testing deep neural networks.
  • Experience in dataset collection and curation for deep learning.
  • Strong communication, collaboration, and organizational skills.
Preferred Qualifications
  • Knowledge of steganography and digital watermarking techniques.
  • Familiarity with image, video, and audio compression algorithms.
  • Publication history in major ML/CV conferences (CVPR, ICCV, NeurIPS, etc.).
  • Experience deploying ML models to mobile, desktop, or cloud-based customer platforms.
Key Concepts (for clarity) Watermarking

Embedding identifiable information into digital media (visible or invisible) to prove ownership, track use, or secure content.

Steganography

Hiding information within media in a way that is undetectable to the human eye or ear. Often used for secure communication or embedding machine-readable signatures.

Media Provenance

Verifying the origin and authenticity of digital content to ensure it hasn’t been altered—important for combating deepfakes and unauthorized edits.

Equal Opportunity Employer

Intratek Computer, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, ancestry, national origin, sex, sexual orientation, age, disability, marital status, domestic partner status, or medical condition.

Veterans Preference

We proudly provide preference to returning war veterans in recognition of their service and skills.

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