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Eeg Machine Learning Jobs (NOW HIRING)

Beacon Biosignals

Algorithm Engineer

Boston, MA · On-site +1

$150K - $170K/yr

For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of ... As part of Beacon's analytics and machine learning domain, you'll work alongside fellow data ...

Ascension

EEG Technician

Milwaukee, WI · On-site

$24.76/hr

... learning * Emotional well-being: Employee Assistance Program, counseling and peer support ... machine. * Review patient's record and instructs patients prior to procedures. Monitor patient ...

Alljoined

Computational Neuroscientist

San Francisco, CA · On-site

$120K - $160K/yr

... imaging data (EEG, fMRI). * Proficiency in Python (MNE, Numpy, PyschoPy) and associated machine learning frameworks (PyTorch, Sci-Py, Scikit-Learn). * Extensive experience using advanced ...

LVIS

Research Scientist

Palo Alto, CA · On-site

$120K - $140K/yr

Strong understanding of machine learning and deep learning algorithms and their applications in ... Experience with neural signal decoding (EEG, ECoG, sEEG) * Experience with signal source ...

LVIS Corporation

Research Scientist

Palo Alto, CA · On-site

$125 - $150/hr

Strong understanding of machine learning and deep learning algorithms and their applications in ... Experience with neural signal decoding (EEG, ECoG, sEEG) * Experience with signal source ...

LVIS

Research Scientist

Palo Alto, CA · On-site

$120K - $140K/yr

Strong understanding of machine learning and deep learning algorithms and their applications in ... Experience with neural signal decoding (EEG, ECoG, sEEG) * Experience with signal source ...

LVIS

Research Scientist

Palo Alto, CA · On-site

$120K - $140K/yr

Strong understanding of machine learning and deep learning algorithms and their applications in ... Experience with neural signal decoding (EEG, ECoG, sEEG) * Experience with signal source ...

Emory University

Post Doctoral Researcher

Atlanta, GA · On-site

$60 - $80/hr

... EEG, EMG, kinematic) recordings in the clinic. These approaches are enhanced by advanced imaging ... Experience with machine learning algorithms NOTE: Position tasks are generally required to be ...

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Eeg Machine Learning information

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How much do eeg machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for eeg machine learning in the United States is $34.48, according to ZipRecruiter salary data. Most workers in this role earn between $26.44 and $40.38 per hour, depending on experience, location, and employer.

What is EEG machine learning?

EEG machine learning refers to the application of machine learning algorithms to analyze and interpret electroencephalogram (EEG) data. EEG measures electrical activity in the brain, and machine learning techniques can help detect patterns, classify brain states, and even predict neurological conditions. This approach is widely used in research, healthcare, and brain-computer interface development to improve diagnostics and understand brain function. Machine learning enhances the accuracy and efficiency of EEG data analysis compared to traditional methods.

What are the key skills and qualifications needed to thrive as an EEG machine learning specialist?

To thrive as an EEG Machine Learning Specialist, you need a strong background in neuroscience or biomedical engineering, expertise in signal processing, and advanced knowledge of machine learning algorithms. Proficiency in tools like Python, MATLAB, TensorFlow, and experience with EEG data acquisition systems are typically required. Critical thinking, attention to detail, and effective communication skills help in interpreting complex brainwave data and collaborating with multidisciplinary teams. These competencies are crucial for developing accurate models that advance neurotechnology and clinical diagnostics.

How do EEG machine learning specialists typically collaborate with neuroscientists and clinicians during a project?

EEG Machine Learning specialists often work closely with neuroscientists to design experiments and interpret neural data, ensuring that machine learning models are aligned with research goals. Collaboration with clinicians is also common, especially when developing diagnostic tools or analyzing patient data, as their input helps validate findings and meet clinical requirements. Regular interdisciplinary meetings and clear communication are key to overcoming challenges related to data quality, labeling, and the translation of results into practical applications.

What is the difference between Eeg Machine Learning vs Eeg Data Analyst?

AspectEeg Machine LearningEeg Data Analyst
Required CredentialsBackground in machine learning, data science, or computer science; often requires programming skillsBackground in data analysis, statistics, or neuroscience; may require knowledge of EEG data processing
Work EnvironmentResearch labs, tech companies, healthcare startups focusing on AI and machine learning applicationsHospitals, research institutions, healthcare organizations analyzing EEG data for diagnostics
Industry UsageDeveloping algorithms for EEG data interpretation, predictive modeling, and automationAnalyzing EEG data to identify patterns, generate reports, and support clinical decisions

While both roles work with EEG data, Eeg Machine Learning focuses on developing algorithms and models using programming and machine learning techniques. Eeg Data Analysts primarily interpret and analyze EEG data to support clinical or research outcomes. The roles overlap in data handling but differ in technical focus and application.

What other helpful pages are available for Eeg Machine Learning?

Other pages related to Eeg Machine Learning:

Infographic showing various Eeg Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $71,720 per year, or $34.5 per hour.

Algorithm Engineer

Boston, MA • On-site, Remote

Beacon Biosignals
Software Development • 1 - 10 employees
Learn more about Beacon Biosignalsexternal

$150K - $170K/yr

Full-time

PTO

Re-posted 7 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 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 robust asynchronous work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston, New York City and Paris.
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 4 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 familiar with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
  • You follow and adopt best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
  • You are familiar 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 $150,000 - $170,000. 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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