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Full Time Brain Computer Interface Jobs (NOW HIRING)

Our translational brain computer interface and pioneering models decode emotion, putting experience and wellbeing at the center of every interaction. Our wearable BCI achieves fMRI-comparable ...

Software Engineer, BCI Applications

Austin, TX ยท On-site

$150K - $281K/yr

Team Description: The Brain Computer Interface (BCI) Applications Team is responsible for ... Base Salary Range: $150,000-$281,000 USD What We Offer: Full-time employees are eligible for the ...

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the University of Michigan's Direct to Brain Interface Laboratory (UM-DBI); our technology, an artificial ...

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the University of Michigan's Direct to Brain Interface Laboratory (UM-DBI); our technology, an artificial ...

Internship Program

New York, NY

$18.25 - $23.75/hr

Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive ... Potential for full-time conversion after graduation

Internship Program

New York, NY

$18.25 - $23.75/hr

Synaptrix is on a mission to revolutionize brain-computer interfaces through non-invasive ... Potential for full-time conversion after graduation

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the University of Michigan's Direct to Brain Interface Laboratory (UM-DBI); our technology, an artificial ...

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How much do full time brain computer interface jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for full time brain computer interface in the United States is $54.94, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $62.50 per hour, depending on experience, location, and employer.

What is a full time brain computer interface professional?

A Full Time Brain Computer Interface (BCI) professional is someone who works exclusively on developing, researching, or implementing technology that enables direct communication between the human brain and external devices. These professionals may come from backgrounds in neuroscience, engineering, computer science, or biomedical fields. Their daily tasks often include designing BCI hardware or software, analyzing brain signals, and collaborating with interdisciplinary teams to improve BCI applications for healthcare, communication, or human augmentation. Full time roles can be found in research institutions, tech companies, and healthcare organizations, focusing on both experimental and real-world BCI solutions.

What are the key skills and qualifications needed to thrive as a brain computer interface engineer?

To thrive as a Brain Computer Interface Engineer, you need a strong background in neuroscience, biomedical engineering, or computer science, often supported by advanced degrees and relevant research experience. Familiarity with signal processing tools (such as MATLAB or Python), machine learning frameworks, and specialized hardware like EEG, ECoG, or implantable devices is typically required. Strong analytical thinking, problem-solving abilities, and effective collaboration skills help candidates stand out in this interdisciplinary field. These competencies are crucial to innovating and safely developing technologies that connect neural activity with external devices, advancing both research and clinical applications.

What are some common challenges faced by professionals working in full time brain computer interface roles, and how can applicants prepare for them?

Professionals in Full Time Brain-Computer Interface roles often encounter challenges such as integrating hardware and software components, ensuring data accuracy, and navigating interdisciplinary collaboration between neuroscientists, engineers, and clinicians. Adapting to rapidly evolving BCI technologies and regulatory standards can also present difficulties. Applicants can prepare by strengthening their technical foundation in neuroscience and engineering, actively seeking out collaborative projects, and staying updated on the latest industry advancements and compliance requirements.
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Infographic showing various Full Time Brain Computer Interface job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 2% Contract, and 1% Nights. Highlights an 75% Physical, 2% Hybrid, and 23% Remote job distribution, with an average salary of $114,265 per year, or $54.9 per hour.

Research Engineer - Brain Computer Interface Models

Zyphra

San Francisco, CA โ€ข On-site

Full-time

Re-posted 8 days ago


Job description

Job Summary:
Zyphra is an artificial intelligence company based in San Francisco, California. They are seeking a Research Engineer - Brain Computer Interface Models to contribute to their BCI work by building open-source EEG and brain-computer interface models, involving data collection, preprocessing, and model training.
Responsibilities:
โ€ข Large-scale EEG model training runs and evaluation
โ€ข Architecture and training methodology ablations and innovations
โ€ข Dataset collection and preprocessing for EEG and other BCI modalities
โ€ข Performance optimization of the training stack
โ€ข Integration of models into real-world BCI applications
Qualifications:
Required:
โ€ข Organized, methodical researcher who can take ownership of a project component, communicate their process clearly, and deliver a working module
โ€ข Excellent communication and collaboration skills, with clean and concise coding practices
โ€ข Strong implementation and prototyping skills, with comfort working across both research and engineering at scale
โ€ข Ability to learn new domains quickly, orient oneself in the academic literature, and implement new ideas, creatively borrowing concepts from other modalities and applying them to EEG domain
โ€ข Interest in neural data such as EEG, MEG, fMRI as well as building foundation models in a much less explored space
โ€ข Proficiency with PyTorch and Python
Preferred:
โ€ข Experience with VAEs, GANs, diffusion models, and contrastive learning
โ€ข Familiarity with signal processing (especially for EEG) and time-series analysis
โ€ข Experience training on large-scale (multi-node) GPU clusters
โ€ข Experience contributing to large existing codebases and ramping up quickly
โ€ข Previously published machine learning research in well-respected venues
Company:
Zyphra is superintelligence research and product company based in San Francisco, California. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.