Work on state of the art generative pipelines for image, video, language or audio generation * Deliver generative machine learning experiences on device * Build cutting-edge augmented reality ...
Work on state of the art generative pipelines for image, video, language or audio generation * Deliver generative machine learning experiences on device * Build cutting-edge augmented reality ...
Research Engineer, Machine Learning Systems
San Francisco, CA ยท On-site +1
$150K - $250K/yr
Even if billions of hours of audio were accessible, its inherent high dimensionality creates ... You'll work at the intersection of machine learning, data infrastructure, and internal tooling to ...
Research Engineer, Machine Learning Systems
San Francisco, CA ยท On-site +1
$150K - $250K/yr
Even if billions of hours of audio were accessible, its inherent high dimensionality creates ... You'll work at the intersection of machine learning, data infrastructure, and internal tooling to ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
$216K - $324K/yr
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
$216K - $324K/yr
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Audio Systems Engineer
Sunnyvale, CA ยท On-site
$144K/yr
Familiarity with audio algorithm development and/or machine learning techniques * 4+ years of experience designing and deploying objective test methodologies for consumer electronics devices and ...
Audio Systems Engineer
Sunnyvale, CA ยท On-site
$144K/yr
Familiarity with audio algorithm development and/or machine learning techniques * 4+ years of experience designing and deploying objective test methodologies for consumer electronics devices and ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
$216K - $324K/yr
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
$216K - $324K/yr
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Research, Audio Expertise
San Francisco, CA ยท On-site
$350K - $475K/yr
You'll explore how audio models enable more natural and efficient communication/collaboration ... Understanding of machine learning fundamentals, large-scale training, and distributed compute ...
Research, Audio Expertise
San Francisco, CA ยท On-site
$350K - $475K/yr
You'll explore how audio models enable more natural and efficient communication/collaboration ... Understanding of machine learning fundamentals, large-scale training, and distributed compute ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Machine Learning Engineer, SIML
Cupertino, CA ยท On-site
Description We are seeking a machine learning research engineer with experience building modern ... audio/multimodal foundation models. You will stay at the forefront of the latest AI research to ...
Machine Learning Engineer, Siri Attention & Invocation
Cupertino, CA ยท On-site
$150K - $225K/yr
Be responsible for developing and integrating Siri's speech and audio experience in a full range of Apple devices. Collaborate with researchers to develop advanced machine learning (ML) technologies.
Machine Learning Engineer, Siri Attention & Invocation
Cupertino, CA ยท On-site
$150K - $225K/yr
Be responsible for developing and integrating Siri's speech and audio experience in a full range of Apple devices. Collaborate with researchers to develop advanced machine learning (ML) technologies.
We are seeking a Machine Learning Architect to serve as a senior technical leader spanning the full ... audio, and text modalities. Direct experience building speech-to-speech conversational systems ...
We are seeking a Machine Learning Architect to serve as a senior technical leader spanning the full ... audio, and text modalities. Direct experience building speech-to-speech conversational systems ...
Senior Machine Learning Engineer
San Francisco, CA ยท On-site
$123K - $169K/yr
Senior Machine Learning Engineer About the Company We are a rapidly scaling, post-revenue ... Construct audio analysis and processing pipelines . * Establish and enhance our MLOps ...
Senior Machine Learning Engineer
San Francisco, CA ยท On-site
$123K - $169K/yr
Senior Machine Learning Engineer About the Company We are a rapidly scaling, post-revenue ... Construct audio analysis and processing pipelines . * Establish and enhance our MLOps ...
Mid-Level Machine Learning Engineer
San Jose, CA ยท On-site
$110K - $200K/yr
Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing. * Implement and optimize ML models on embedded platforms, including FPGA ...
Mid-Level Machine Learning Engineer
San Jose, CA ยท On-site
$110K - $200K/yr
Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing. * Implement and optimize ML models on embedded platforms, including FPGA ...
Mid-Level Machine Learning Engineer
San Jose, CA ยท On-site
$110K - $200K/yr
Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing. * Implement and optimize ML models on embedded platforms, including FPGA ...
Mid-Level Machine Learning Engineer
San Jose, CA ยท On-site
$110K - $200K/yr
Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing. * Implement and optimize ML models on embedded platforms, including FPGA ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Machine learning research at Netflix improves various aspects of our business, including ... Modeling across text/image/video/audio, modality fusion and alignment, multimodal retrieval * Model ...
Audio Systems Engineer, Robot Head
San Carlos, CA ยท On-site
$173K - $240K/yr
This team works across hardware, firmware, machine learning, software, industrial design, and manufacturing to deliver robust audio experiences that perform reliably inside homes and alongside people.
Audio Systems Engineer, Robot Head
San Carlos, CA ยท On-site
$173K - $240K/yr
This team works across hardware, firmware, machine learning, software, industrial design, and manufacturing to deliver robust audio experiences that perform reliably inside homes and alongside people.
Audio Machine Learning information
See California salary details
$29.1K - $41.9K
16% of jobs
$47.7K is the 25th percentile. Wages below this are outliers.
$41.9K - $54.6K
19% of jobs
$54.6K - $67.3K
13% of jobs
The median wage is $68.8K / yr.
$67.3K - $80.1K
14% of jobs
$80.1K - $92.8K
10% of jobs
$98.7K is the 75th percentile. Wages above this are outliers.
$92.8K - $105.6K
6% of jobs
$105.6K - $118.3K
4% of jobs
$118.3K - $131K
5% of jobs
$131K - $143.8K
4% of jobs
$143.8K - $156.5K
8% of jobs
$156.5K - $169.3K
0% of jobs
$29.1K
$83.3K
$169.3K
How much do audio machine learning jobs pay per year?
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 California?
The most popular types of Audio Machine Learning jobs in California are:
What are popular job titles related to Audio Machine Learning jobs in California?
For Audio Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning jobs in California look for?
The top searched job categories for Audio Machine Learning jobs in California are:
What cities in California are hiring for Audio Machine Learning jobs?
Cities in California with the most Audio Machine Learning job openings:

Machine Learning Engineer, Generative ML, Level 4
Palo Alto, CA โข On-site
Full-time
Medical
Posted 20 days ago
Job description
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.
The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.
Snap's Generative ML Platform team builds cutting-edge AI technologies that power creative, scalable experiences for hundreds of millions of Snapchatters worldwide. From multimodal LLMs and video generation to real-time AR, human understanding, and 3D content creation, we develop the full stack of generative AI, including foundational models, efficient infrastructure, and on-device and server-side inference. Our team creates intuitive tools, platforms, and agentic systems that empower creators, developers, and internal teams to bring ideas to life, while advancing personalized, human-centric experiences across mobile, web, and wearable devices like Spectacles.
We're looking for a Machine Learning Engineer to join our Generative ML team!
What you'll do:
Develop innovative machine learning technology and products that serve millions of Snapchatters
Work on state of the art generative pipelines for image, video, language or audio generation
Deliver generative machine learning experiences on device
Build cutting-edge augmented reality experiences using generative and diffusion models
Partner with cross-functional Snap teams to explore and prototype new products
Knowledge, Skills & Abilities:
A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
Strong software development skills in Python or C++
Proficiency working with major deep learning frameworks: PyTorch or TensorFlow
Knowledge of mathematics and deep learning foundations
Desire to solve open ambiguous problems
Desire to grow professionally, learn and help others
Ability to effectively collaborate with internal teams and external partners
Ability to work independently
Minimum Qualifications:
Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
Research or engineering experience in one or more of the following: generative models, efficient models, diffusion models, language models, or other related applications of machine learning
Preferred Qualifications:
Master's degree or PhD in a related technical field
Experience developing real-time software for mobile applications
Knowledge of GenAI, especially image, video, language and audio generation foundations
Knowledge of efficient model foundations
Track record of successful projects in GenAI field
Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.
If you have a disability or special need that requires accommodation, please don't be shy and provide us some information.
"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).
Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success!
Compensation
In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.
Zone A (CA, WA, NYC):
The base salary range for this position is $173,000-$259,000 annually.Zone B:
The base salary range for this position is $164,000-$246,000 annually.Zone C:
The base salary range for this position is $147,000-$220,000 annually.This position is eligible for equity in the form of RSUs.About Snapchat for Business
Sourced by ZipRecruiter
Industry
Marketing
Company size
1,001 - 5,000 Employees
Headquarters location
Santa Monica, CA, US
Year founded
2011