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Remote Audio Signal Processing Jobs in Massachusetts

Destination Careers

Remote Travel Coordinator

Boston, MA · On-site +1

$40K - $70K/yr

... signals in application materials based on available information. These tools assist our recruitment ... If you would like more information about how your data is processed, please contact us.

Destination Careers

Remote Travel Coordinator

Boston, MA · Remote

$40K - $70K/yr

... signals in application materials based on available information. These tools assist our recruitment ... If you would like more information about how your data is processed, please contact us. apply for ...

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All JobsAudio Signal Processing JobsRemote Audio Signal Processing JobsRemote Audio Signal Processing Jobs in Massachusetts

Remote Audio Signal Processing information

What is remote audio signal processing?

Remote audio signal processing refers to the analysis, modification, and enhancement of audio signals using digital algorithms, typically performed from a location different from where the audio was recorded or is being used. Professionals in this field work with technologies such as noise reduction, echo cancellation, audio compression, and effects processing, often leveraging cloud-based tools and platforms. This allows for real-time audio improvements or transformations in applications like teleconferencing, streaming, and music production, all managed remotely.

What are the key skills and qualifications needed to thrive as a remote audio signal processing engineer?

To excel as a Remote Audio Signal Processing Engineer, you need strong knowledge of digital signal processing (DSP), audio algorithms, and programming skills, typically supported by a degree in electrical engineering, computer science, or a related field. Expertise in tools like MATLAB, Python, C++, and familiarity with platforms such as JUCE or VST, as well as experience with audio editing and analysis software, is highly valuable. Excellent problem-solving, communication, and self-motivation are essential soft skills for managing tasks independently and collaborating with distributed teams. These skills and qualifications are critical for developing high-quality audio solutions and ensuring effective project delivery in a remote work environment.

What are some common challenges faced by professionals in remote audio signal processing roles, and how can they be addressed?

Professionals in remote audio signal processing often encounter challenges such as latency issues, inconsistent audio quality due to varying internet connections, and difficulties in real-time collaboration with team members or clients. To address these, it’s important to use reliable communication platforms, leverage cloud-based audio tools that support version control, and establish clear file-sharing protocols. Regular virtual meetings and clear documentation can also help ensure smooth collaboration and consistent project outcomes.

What is the difference between Remote Audio Signal Processing vs Remote Audio Engineering?

AspectRemote Audio Signal ProcessingRemote Audio Engineering
CredentialsKnowledge of audio algorithms, signal processing certificationsAudio engineering certifications, experience with recording/mixing
Work EnvironmentPrimarily software-based, focused on digital signal manipulationStudio or live sound environments, often involving hardware setup
Industry UsageTech companies, software development, audio tech startupsMusic production, broadcasting, live events
Search & Comparison IntentFocus on technical signal processing skillsFocus on audio production and engineering expertise

Remote Audio Signal Processing involves developing and applying algorithms to manipulate audio signals digitally, often requiring programming and technical skills. Remote Audio Engineering focuses on capturing, mixing, and producing audio content, emphasizing hands-on technical and creative skills. While both roles work remotely and in the audio industry, their core responsibilities and skill sets differ significantly.

What are popular job titles related to Remote Audio Signal Processing jobs in Massachusetts?

For Remote Audio Signal Processing jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Remote Audio Signal Processing jobs in Massachusetts look for?

The top searched job categories for Remote Audio Signal Processing jobs in Massachusetts are:

What cities in Massachusetts are hiring for Remote Audio Signal Processing jobs?

Cities in Massachusetts with the most Remote Audio Signal Processing job openings:

Remote Audio Signal Processing jobs near you
Infographic showing various Remote Audio Signal Processing job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Senior Algorithm Engineer

Beacon Biosignals

Boston, MA • On-site, Remote

$170K - $190K/yr

Full-time

PTO

Re-posted 20 days ago

Job description

Beacon Biosignals is transforming precision medicine for the brain, from clinical development to clinical care. For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our Diagnostics business is building the most comprehensive at-home platform for precision diagnostics, combining EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders. Together, we're changing the way patients are diagnosed and treated for any disorder that affects brain physiology.
Beacon Biosignals is seeking a Senior Algorithm and Machine Learning engineer!
As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data scientists, neuroscientists, engineers, and clinicians to scope, build, deploy, and maintain the machine and deep learning models that analyze brain and biosignal data for advancing sleep, neurological, and psychiatric therapy development.
At Beacon, we've found that cultural and scientific impact is driven most by those who lead by example. As such, we're always seeking out new contributors whose work demonstrates innate curiosity, a bias toward simplicity, an eye for composability, a self-service mindset, and-most of all-a deep empathy toward colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.
Beacon's work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston, New York City and Paris. This is a fully remote role based anywhere in the U.S.
What success looks like
  • Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation.
  • Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.
  • Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation.
  • Spread and improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing.
  • Present results to key stakeholders and assist them in utilizing algorithms for client engagement.
  • Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development.

What you will bring
  • You have more than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production.
  • You are experienced with digital signal processing (DSP) and statistics and care about using the right tool for the job, which in many cases might not be machine learning or deep learning.
  • You are proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
  • You are proficient with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
  • You follow and spread best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
  • You are experienced with biosignals, medical imaging data, or large time-series datasets, or are enthusiastic about learning more in the domain.
  • You thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.
  • You are able to distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally.
  • You are excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms.

The US-based salary range for this role is $170,000 - $190,000. Salary ranges are determined using current market compensation data for this role and adjusted based on experience, skills, and location. The base salary is one component of the total compensation package, which includes equity, PTO and other benefits.
At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.
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