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Eeg Machine Learning Jobs (NOW HIRING)

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

You will design and implement advanced machine learning models for EEG-based neural decoding, contribute to high-impact research, and help build the foundational infrastructure behind our brain ...

Neurable, INC

Machine Learning

Cambridge, MA · On-site

Experience working with real-time data, large datasets, brain-computer Interface, and/or EEG data ... in various machine and deep learning applications/design especially regarding neural networks ...

Neurable, INC

Machine Learning

Cambridge, MA · On-site

Experience working with real-time data, large datasets, brain-computer Interface, and/or EEG data ... in various machine and deep learning applications/design especially regarding neural networks ...

Trinity Health

EEG Technician

Grand Rapids, MI · On-site

... learning, intranet and computer navigation. Ability to use other software required to perform ... all machines, in a safe and proper manner. • Performs all clerical and support functions ...

Trinity Health

EEG Technician

Grand Rapids, MI · On-site

... learning, intranet and computer navigation. Ability to use other software required to perform ... all machines, in a safe and proper manner. • Performs all clerical and support functions ...

Trinity Health

EEG Technician

Grand Rapids, MI · On-site

... learning, intranet and computer navigation. Ability to use other software required to perform ... all machines, in a safe and proper manner. • Performs all clerical and support functions ...

Ceribell, Inc

Senior/Staff Data Scientist

Sunnyvale, CA · On-site

... EEG neurodiagnostics to the next level. What you'll do: * Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various ...

Synaptrix Labs

Internship Program

New York, NY · On-site

$18.25 - $23.75/hr

Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement. * Develop intuitive interfaces and user experiences for individuals with mobility or ...

Synaptrix Labs

Internship Program

New York, NY

$18.25 - $23.75/hr

Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement. * Develop intuitive interfaces and user experiences for individuals with mobility or ...

Synaptrix Labs

Internship Program

New York, NY

$18.25 - $23.75/hr

Design, train, and evaluate machine learning models for EEG/EMG decoding, denoising, and signal enhancement. * Develop intuitive interfaces and user experiences for individuals with mobility or ...

Ceribell, Inc

Senior/Staff Data Scientist

Sunnyvale, CA · On-site

$184K - $200K/yr

... EEG neurodiagnostics to the next level. What you'll do: * Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various ...

Ceribell, Inc

Senior/Staff Data Scientist

San Francisco, CA · On-site

$184K - $200K/yr

... EEG neurodiagnostics to the next level. What you'll do: * Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various ...

Ceribell, Inc

Senior/Staff Data Scientist

San Jose, CA · On-site

$184K - $200K/yr

... EEG neurodiagnostics to the next level. What you'll do: * Use time-series analysis, statistical signal processing and machine learning techniques to design classification algorithms for various ...

Dell Medical School

Research Associate II

Austin, TX · On-site

$47K/yr

Demonstrated expertise in EEG-based brain-computer interfaces (BCIs). * Knowledge of signal processing, machine learning, statistical analysis, and scientific research methodologies. * Ability to ...

Beacon Biosignals

Senior Algorithm Engineer

Boston, MA · On-site +1

$170K - $190K/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 ...

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Eeg Machine Learning information

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$34

$54

How much do eeg machine learning jobs pay per hour?

As of Sep 8, 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.

Machine Learning Researcher

San Francisco, CA • On-site

Alljoined
See more jobs at Alljoinedexternal

$140K - $250K/yr

Full-time

Medical

Re-posted 5 days ago

Job description

About Alljoined
Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale neural datasets to decode internal thought directly. By advancing the frontier of neural decoding, we aim to unlock meaningful breakthroughs in human wellness and capability.
About the Role
We are looking for a talented Machine Learning Researcher to join our core R&D team. You will design and implement advanced machine learning models for EEG-based neural decoding, contribute to high-impact research, and help build the foundational infrastructure behind our brain-decoding systems.
You will work closely with leading experts in neural decoding and AI to push the boundaries of what is possible in brain-computer interfaces. This role sits at the intersection of ambitious research and rigorous engineering: you will explore novel modeling approaches while translating promising ideas into reliable, production-quality systems.
What You'll Work On
  • Develop, train, and refine state-of-the-art deep learning models for neural decoding, drawing on recent advances in architectures such as transformers and diffusion models.
  • Explore novel methods for modeling high-frequency, time-series EEG data alongside several adjacent data modalities.
  • Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
  • Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end neural-decoding systems.
  • Publish findings at leading machine learning and AI conferences, including NeurIPS, ICML, ICLR, and CVPR.
  • Contribute to open-source communities where appropriate.
You May Be a Good Fit If You Have
  • A bachelor's degree in computer science or a related field-such as artificial intelligence, computational neuroscience, mathematics, or biomedical engineering-and five to seven years of experience in machine learning research or applied machine learning engineering; or
  • A graduate degree (M.S. or Ph.D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical engineering-and at least three years of experience in machine learning research or applied machine learning engineering.
  • A track record of high-quality research, demonstrated through publications at leading machine learning conferences or in respected journals, including NeurIPS, ICML, ICLR, or CVPR.
  • Strong proficiency in Python and PyTorch, along with familiarity with modern machine learning tooling and distributed training.
  • Experience contributing to a production-quality codebase with modern code-review standards.

Candidates with a Ph.D. and/or experience working in a high-profile machine learning research lab are strongly preferred.
Areas of Relevant Expertise
We are particularly interested in candidates with experience in one or more of the following areas:
  • Multimodal representation learning: CLIP-style contrastive objectives and masked autoencoding.
  • Generative modeling: Diffusion models, transformer decoders, and latent GANs.
  • Temporal sequence modeling: State-space models, STFT-aware transformers, and RWKV.

Benefits
  • Options for housing support
  • Visa sponsorship
  • Health insurance

Apply