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Audio Machine Learning Jobs (NOW HIRING)

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

Jeppesen ForeFlight is seeking a Senior Machine Learning Engineer to help build and scale domain-specialized automatic speech recognition (ASR) systems for aviation and operational audio workflows.

Machine Learning Engineer

Clifton Park, NY · On-site

$85K - $125K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

OR

$523K - $920K/yr

We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and ... Responsibilities Lead a broad portfolio of end-to-end initiatives in multimodal LLM and audio ...

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry ... audio cues. When successful, your research will be deployed into millions of vehicles worldwide.

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

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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 Engineer II

Machine Learning Engineer II

Milwaukee Tool

Brookfield, WI

Full-time

Medical, Dental, Vision, Retirement

Posted 22 days ago


Job description

Job Description:

Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.

At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions on our engineering teams. Our Engineering Team is responsible for giving life to the batteries, motors, and electronics that power solutions changing the lives of our users. Every developmental phase of these critical components happens in-house under the watch of this team. We continue to invest in engineering resources to design and develop leadership in electronic capabilities; something unique within the industry. And we're pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.

Your role on our team

As a Machine Learning Engineer II, you will create, develop, and validate machine learning models while working with highly cross-functional teams to make power tool solutions that change the lives of our users. You will innovate and explore new machine learning solutions to deploy into Milwaukee products around the world while demonstrating excellent problem-solving skills, critical thinking, and the ability to thrive under pressure in a dynamic environment. Success in this role also requires strong technical communication skills and fundamental project management abilities, along with a proactive sense of ownership for projects and tasks and an understanding of how they connect to broader initiatives.

What TOOLS you'll bring with you:

  • Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
  • Completed course work or specialization in Machine Learning and/or Data Science
  • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field
  • Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
  • Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
  • Proficient developing and debugging code in Python
  • Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
  • Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
  • Sold mathematical foundation in statistics, linear algebra, calculus and optimization
  • Experience working with modern software development tools and version control tools
  • Excellent problem-solving skills, critical thinking, and ability to work well under pressure in a dynamic environment.
  • Excellent technical communication skills and fundamental project management abilities
  • Demonstrated strong sense of ownership of a project or tasks and understanding of relationships to other tasks/projects
  • Ability to travel up to 10% of the time (domestic and international).

Other TOOLS we prefer you to have:

  • Master's degree or PhD in Machine Learning or related field is preferred
  • At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field (an advanced degree may count toward some experience)
  • Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
  • Proven track record of developing, deploying and implementing AI or ML solutions connected to business objectives
  • Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
  • Working knowledge of various sensor technologies (e.g. IMU, thermistors, magnetic and optical) and interfacing to microcontrollers
  • Working knowledge of embedded systems architecture (HW & SW), microcontroller design and operation
  • Experience with different types of data collection methods, understanding their principles and demonstrating their value in relevant environments
  • Experience developing and deploying machine learning algorithms to edge environments
  • Demonstrated ability to develop robust MLOps pipelines and ensure efficient deployment, monitoring and scaling of ML models

We provide these great perks and benefits:

  • Robust health, dental and vision insurance plans.
  • Generous 401 (K) savings plan.
  • Education assistance.
  • On-site wellness, fitness center, food, and coffee service.
  • And many more, check out our benefits site HERE.

Milwaukee Tool is an equal opportunity employer.