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Audio Machine Learning Jobs (NOW HIRING)

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP * 2+ years experience managing machine learning teams * You have an ability to understand and make ...

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

Design, train, evaluate, and deploy machine learning models across text, image, audio, and multimodal domains. * Develop and improve classification systems for safety, security, abuse detection, and ...

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

Machine Learning Engineer

Somerville, MA · On-site

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

Machine Learning Engineer

Somerville, MA · On-site +1

$170K - $200K/yr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice ... Experience with audio models or speech systems (ASR, TTS, speaker modeling, etc.) * Experience with ...

You will explore Picture Quality (PQ) and Audio Quality (AQ) improvements using AI in a resource ... Hands-on experience with Machine Learning / Deep Learning frameworks like TensorFlow or PyTorch

Research and develop advanced machine learning solutions for natural language processing (NLP), audio, computer vision, and multi-modal applications. Work closely with crossfunctional partners ...

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a ...

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

If you're excited about the future of video, audio, video content moderation, and more then you ... A degree in Computer Science, Machine Learning, or a related field, or equivalent professional ...

Design, develop, and deploy deep-learning-based and classical DSP audio algorithms for our SPU ... Desired Skills and Experience Deep learning, Machine learning, DSP, Python, PyTorch Benefits ...

Senior Machine Learning Engineer

Manhattan, NY · On-site

$133K - $176K/yr

If you're excited about the future of video, audio, video content moderation, and more then you ... A degree in Computer Science, Machine Learning, or a related field, or equivalent professional ...

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Audio Machine Learning information

See salary details

$29.5K

$84.5K

$171.5K

How much do audio machine learning jobs pay per year?

As of Jul 9, 2026, the average yearly pay for 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 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.
More about Audio Machine Learning jobs
What cities are hiring for Audio Machine Learning jobs? Cities with the most 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 Audio Machine Learning jobs? States with the most job openings for Audio Machine Learning jobs include:
Machine Learning Manager

Machine Learning Manager

Hive

Seattle, WA • On-site

$180K - $250K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 10 days ago


Job description

About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Machine Learning Manager
In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production.
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements
  • Undergraduate or graduate degree in computer science or similar technical field
  • 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements

Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.
Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.