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Audio Machine Learning Jobs in Pennsylvania (NOW HIRING)

... Machine Learning, or relevant technical field. Degree must be completed prior to joining Meta * Experience in multi-modal learning, combining vision, audio, language, or related areas * Experience ...

Research Scientist, Multi-Modal

Pittsburgh, PA ยท On-site

$122K - $181K/yr

... Machine Learning, or relevant technical field. Degree must be completed prior to joining Meta โ€ข Experience in multi-modal learning, combining vision, audio, language, or related areas โ€ข ...

Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis) * Experience and knowledge in cybersecurity best practices

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Audio Machine Learning information

See Pennsylvania salary details

$29.6K

$84.7K

$171.9K

How much do audio machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for audio machine learning in Pennsylvania is $84,658.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $113,300.00 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 Pennsylvania? The most popular types of Audio Machine Learning jobs in Pennsylvania are:
What are popular job titles related to Audio Machine Learning jobs in Pennsylvania? For Audio Machine Learning jobs in Pennsylvania, the most frequently searched job titles are:

Deep Learning Engineer II (Multiple Positions) (REF286216I)

Bosch Group

Pittsburgh, PA โ€ข On-site

$77K - $104K/yr

Full-time

Re-posted yesterday


Job description

Company Description
Robert Bosch LLC seeks Deep Learning Engineer II (Multiple Positions) at its facility located at 2555 Smallman Street, Suite 300, Pittsburgh, PA 15222. Conduct research and advanced development of innovative signal processing and deep learning systems specifically designed to process and analyze sensor signals. These sensor signals include, but are not limited to, audio, vibration, ultrasounds, radar, lidar, power traces, and torque. Utilize expertise in machine learning and signal processing to develop innovative algorithms that accurately interpret and respond to these diverse types of data. Manage the development of artificial intelligence (AI) systems integrated with large language models. These AI systems support agentic workflows, automating complex tasks typically performed by human agents. Work on creating multimodal retrieval-augmented generation applications, combining multiple forms of data (e.g., text, images, audio) to enhance the system's ability to generate relevant and contextually appropriate responses. Collaborate with teams across the organization worldwide to ensure the successful implementation and deployment of these advanced AI solutions on embedded platforms. REQS: This position requires a master's degree or foreign equivalent in Information Technology, Electronic Engineering or a related field and 3 years of experience as a Deep Learning Engineer, Research Engineer or occupation involving design, development, and maintenance of deep learning pipelines for acoustic and vibration signals. Additionally, the applicant must have employment experience with: (1) Deep learning and signal processing frameworks in Python; (2) PyTorch and Lightning; (3) MLFlow and Numpy; (4) Scipy; and (5) Matplotlib. Telecommuting: Hybrid, 2 days per week WFH. Applicants who are interested in this position should apply https://www.bosch.us/careers/, search [Deep Learning Engineer II (Multiple Positions) / REF286216I]
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