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Audio Machine Learning Jobs in California (NOW HIRING)

Description We are seeking a highly capable and dynamic Machine Learning Engineer to work cross-functional in building out a GenAI system in support of Beats and Apple Audio products. The ideal ...

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 ...

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Audio Machine Learning information

See California salary details

$29.1K

$83.3K

$169.3K

How much do audio machine learning jobs pay per year?

As of Jul 1, 2026, the average yearly pay for audio machine learning in California is $83,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,300.00 and $111,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?

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.

Will MLE be replaced by AI?

In the context of an Audio Machine Learning (ML) role, AI tools and automation are increasingly used to assist with tasks like data processing and model deployment. However, MLE professionals are essential for designing, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Human expertise remains critical for interpreting results and ensuring system performance.

What are the typical daily responsibilities of someone working in Audio Machine Learning?

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 is an Audio Machine Learning job?

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.

Which 5 jobs will survive AI?

Audio Machine Learning specialists are likely to continue in demand as AI advances because their expertise in developing and refining audio recognition systems requires specialized skills that are difficult to automate fully. Roles involving creative audio design, audio engineering, and human oversight of AI systems are also expected to persist. These jobs often require a combination of technical knowledge, domain expertise, and critical thinking that AI cannot easily replace.

What engineer makes $500,000 a year?

Senior audio machine learning engineers with extensive experience, advanced skills in deep learning and signal processing, and often working at large tech companies or specialized research labs can earn salaries approaching or exceeding $500,000 annually. Compensation typically includes base salary, bonuses, and stock options, especially in high-demand industries like AI and audio processing.

Do audio engineers get paid well?

Audio engineers typically earn competitive salaries that vary based on experience, location, and industry sector. Entry-level positions may start lower, but experienced professionals working in recording studios, broadcasting, or live sound often have higher earnings, especially with specialized skills and certifications. Overall, the profession offers the potential for good compensation, particularly for those with technical expertise and a strong portfolio.
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 cities in California are hiring for Audio Machine Learning jobs? Cities in California with the most Audio Machine Learning job openings:
Infographic showing various Audio Machine Learning job openings in California as of June 2026, with employment types broken down into 3% As Needed, 80% Full Time, 11% Part Time, 1% Temporary, and 5% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $83,350 per year, or $40.1 per hour.
Machine Learning Manager - Localization Algorithms

Machine Learning Manager - Localization Algorithms

Netflix

Los Angeles, CA

$523K - $920K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 24 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

59th of 67 rated media


Job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next.

The Localization Data Science and Engineering team is at the forefront of removing language barriers and providing a stellar member experience to all our members regardless of their language preferences. We are responsible for the translation and cultural adaptation of all aspects of member interaction, including beautiful localized user interfaces, subtitles, and dubbing of award-winning Netflix originals.

We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and Machine Learning Engineers working on multimodal LLM and audio algorithms. You will support a highly talented team in developing cuttingedge algorithms and systems, and collaborate closely with crossfunctional partners to enhance localization experiences for Netflix members around the world.

Responsibilities
  • Lead a broad portfolio of end-to-end initiatives in multimodal LLM and audio algorithms to achieve Netflix's ambitious localization goals.

  • Mentor, support, and inspire a team of Research Scientists and Machine Learning Engineers, amplifying their impact and fostering their career growth.

  • Partner with technical leads on defining area strategy, planning and executing projects, and developing talent.

  • Set and operationalize a high bar for both execution speed and quality, while nurturing a culture of exceptional technical excellence.

  • Bring cutting-edge technical expertise and build deep domain knowledge to uncover new opportunities and make strategic bets.

  • Build strong relationships with cross-functional, cross-domain partners to shape long-term collaborations and shared visions.

  • Act as a functional leader and domain expert, representing the team's work and strengthening the team's internal and external brand.

  • Contribute to the growth and upskilling of the broader Machine Learning community at Netflix.

About you
  • Proven track record of successfully leading highly technical ML research and engineering teams in multimodal LLMs, speech recognition and understanding, and generative speech.

  • Highly proficient in multimodal LLM and speech algorithm research, and deeply committed to staying current with the latest technical developments; have led teams to launch and continuously improve production ML services.

  • Passionate about leading teams through ambiguous and complex technical and business challenges; focused on bringing clarity, structure, and effective execution.

  • Strong track record in mentoring and developing talent, with proven success recruiting researchers and engineers at multiple levels.

  • Master's or PhD in Machine Learning, Computer Science, or a closely related field.

  • 6+ years of hands-on ML experience (or 4+ years with a relevant PhD).

  • 2+ years of experience leading ML teams.

  • Exceptional verbal and written communication skills.

  • Deeply committed to delivering end-to-end business impact.

  • Netflix culture resonates with you.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $523,000.00 - $920,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.


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About Netflix

Sourced by ZipRecruiter

Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

Industry

Arts, entertainment, and recreation

Company size

5,001 - 10,000 Employees

Headquarters location

Los Gatos, CA, US

Year founded

1997