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Brain Machine Interface Jobs in California (NOW HIRING)

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

About the Role We're seeking a talented Machine Learning Researcher to join our core R&D team. This ... possible in brain computer interfaces. Key Responsibilities * Research & Model Development:

Neuralink

Neuroengineer, Next Gen

Fremont, CA

... brain-computer interfaces. We are laying the groundwork for intuitive, high-dimensional, and bidirectional interfaces between brains and machines, with the goal of helping people challenged by a ...

Neuralink

Neuroengineer Intern

South San Francisco, CA · On-site

$35/hr

... brain-computer interfaces. We are laying the groundwork for intuitive, high-dimensional, and bidirectional interfaces between brains and machines, with the goal of helping people challenged by a ...

Neuralink

Neuroengineer Intern

South San Francisco, CA

$35/hr

... brain-computer interfaces. We are laying the groundwork for intuitive, high-dimensional, and bidirectional interfaces between brains and machines, with the goal of helping people challenged by a ...

Neuralink

Neuroengineer, Next Gen

Fremont, CA · On-site

$122K - $226K/yr

... brain-computer interfaces. We are laying the groundwork for intuitive, high-dimensional, and bidirectional interfaces between brains and machines, with the goal of helping people challenged by a ...

Alljoined

Research Intern (Fall)

San Francisco, CA · On-site

$30/hr

... breakthrough brain-computer interface research. You'll work at the intersection of neuroscience and machine learning, developing and optimizing pipelines that process massive EEG datasets and ...

Paradromics

Research Engineer

Oakland, CA · On-site

$120K - $150K/yr

Paradromics is building a brain-computer interface (BCI) platform that records brain activity at ... Familiarity with machine learning concepts and experience collaborating with machine learning ...

Paradromics, Inc.

Research Engineer

Oakland, CA · On-site

Paradromics is building a brain-computer interface (BCI) platform that records brain activity at ... Familiarity with machine learning concepts and experience collaborating with machine learning ...

Alljoined

Computational Neuroscientist

San Francisco, CA · On-site

$120K - $160K/yr

... from the brain, entirely non-invasively. We apply deep learning research to large scale EEG ... Our goal is to develop a general consumer interface to completely transform how we can live our ...

Neara

Vice President of Market Access

Santa Clara, CA · On-site

$200 - $250/hr

... brain-computer interface (BCI) to heal and empower millions of people living with neurological ... Our team brings together experts in neurosurgery, AI and machine learning, microfabrication ...

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Brain Machine Interface information

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How much do brain machine interface jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for brain machine interface in California is $22.52, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $25.14 per hour, depending on experience, location, and employer.

What are the career paths in neurolinguistics?

Career paths in neurolinguistics include roles such as research scientist, clinical neuropsychologist, speech-language pathologist, and cognitive neuroscientist. These positions often require advanced degrees like a master's or Ph.D., along with skills in neuroimaging, data analysis, and understanding of language processing in the brain.

Is there a high demand for neuroscientists?

Neuroscientists, including those working on brain-machine interfaces, are in increasing demand due to advancements in neurotechnology and the growing need for research in neural disorders and brain-computer communication. Employment opportunities are expected to grow as interdisciplinary skills in neuroscience, engineering, and data analysis become more valuable in both academia and industry. Certifications in neuroimaging or programming can enhance job prospects in this field.

What are the typical daily responsibilities of someone working in a Brain Machine Interface position?

Professionals in Brain Machine Interface roles usually divide their time between designing experiments, analyzing neural data, developing and testing interface prototypes, and collaborating with cross-disciplinary teams such as neuroscientists, engineers, and clinicians. They may also be involved in writing technical documentation, participating in regulatory compliance activities, and keeping up with the latest scientific literature. Depending on the project, work can flow between laboratory research and computational tasks, requiring flexibility and an eagerness to learn new techniques. The environment is often collaborative and research-focused, providing ample opportunities to contribute to exciting advancements in neurotechnology.

What are the key skills and qualifications needed to thrive in the Brain Machine Interface position, and why are they important?

To thrive in a Brain Machine Interface (BMI) role, you need a strong background in neuroscience, biomedical engineering, computer science, or a related field, often supported by advanced degrees or specialized training. Proficiency with signal processing software (such as MATLAB or Python), brain imaging tools, and hardware prototyping is typically required, along with familiarity with regulatory standards. Strong problem-solving skills, collaboration, and attention to detail help individuals excel in multi-disciplinary teams working at the intersection of biology and technology. These competencies are crucial for developing safe, effective interfaces and driving innovation in this fast-evolving field.

Are BCIs the future?

Brain Machine Interface (BMI) technology is advancing rapidly, with applications in medical rehabilitation, neuroprosthetics, and human-computer interaction. As research progresses, BCIs are expected to become more integrated into healthcare and consumer devices, potentially transforming how humans interact with technology in the future.

What jobs can I get with HCI?

With expertise in Human-Computer Interaction (HCI), you can pursue roles such as UX designer, usability analyst, interaction designer, or research scientist. These jobs often require skills in user-centered design, prototyping tools, and understanding of cognitive psychology or ergonomics.

What is a Brain Machine Interface job?

A Brain Machine Interface (BMI) job involves developing technologies that connect the human brain with computers or external devices. Professionals in this field work on designing, testing, and improving neural interfaces to restore lost sensory or motor functions, enhance cognitive abilities, or enable direct brain communication with machines. Roles may include neuroscientists, engineers, and software developers collaborating to advance BMI applications in healthcare, assistive technology, and neuroprosthetics.

What are the most commonly searched types of Brain Machine Interface jobs in California? The most popular types of Brain Machine Interface jobs in California are:
What are popular job titles related to Brain Machine Interface jobs in California? For Brain Machine Interface jobs in California, the most frequently searched job titles are:
What job categories do people searching Brain Machine Interface jobs in California look for? The top searched job categories for Brain Machine Interface jobs in California are:
What cities in California are hiring for Brain Machine Interface jobs? Cities in California with the most Brain Machine Interface job openings:
Brain Machine Interface jobs near you
Infographic showing various Brain Machine Interface job openings in California as of July 2026, with employment types broken down into 5% As Needed, 64% Full Time, 26% Part Time, 2% Temporary, and 3% Contract. Highlights an 97% Physical, and 3% Remote job distribution, with an average salary of $46,846 per year, or $22.5 per hour.

Machine Learning Researcher

Alljoined

San Francisco, CA • On-site

$140K - $250K/yr

Full-time

Medical, Retirement

Re-posted 12 days ago

Job description

About Alljoined
Alljoined aims to solve the communication bottleneck between humans and technology by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale EEG datasets collected on affordable hardware to decode images, text, and video initially, and eventually moving to internal thought. We are state-of-the art in capabilities and are fully vertically integrated. Our goal is to develop a general consumer interface to completely transform what we can do at home and work.
We are actively growing our world-class team of researchers to build the next interface to improve individual lives as well as the well-being of society as a whole.
About the Role
We're seeking a talented Machine Learning Researcher to join our core R&D team. This role involves designing and implementing advanced machine learning models for EEG-based neural decoding, publishing high-impact research, and developing the core infrastructure for our brain decoding systems. You will work closely with leading experts in neural decoding and AI, pushing the boundaries of what's possible in brain computer interfaces.
Key Responsibilities
  • Research & Model Development:
    • Develop, train, and refine state-of-the-art deep learning models for neural decoding, building on the latest advancements in ML architectures (e.g., transformers, diffusion models, etc).
    • Explore novel approaches for modeling high-frequency timeseries EEG datasets along with a number of adjacent data modalities.
    • Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
  • Collaboration & Publication:
    • Collaborate with a team of neuroscientists and ML engineers to create scalable, end-to-end neural decoding solutions.
    • Publish findings at top-tier ML and AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR) and contribute to open-source communities where appropriate.

Qualifications
  • Educational Background & Experience:
    • Bachelor's degree in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Mathematics, Biomedical Engineering, etc), with 5-7 years of experience in ML research or applied ML engineering; OR
    • Graduate degree (M.S., Ph.D.) in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Biomedical Engineering) with 3+ years of experience in ML research or applied ML engineering.
    • Candidates with a Ph.D. and/or experience in high profile ML research labs are strongly preferred.
  • Technical Expertise:
    • Multimodal Representation Learning (CLIP-style contrastive objectives, masked autoencoding)
    • Generative Modeling (diffusion, transformer-decoders, latent-GANs)
    • Temporal Sequence Modeling (state-space models, STFT-aware transformers, RWKV)
    • A track record of high-quality research demonstrated by publications in top ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).
    • Strong proficiency in Python and PyTorch, familiarity with ML tooling, and distributed training.
    • Experience working in a production-quality codebase with modern code review standards.

Compensation Range
$140,000 - $250,000/year + equity
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range.
Benefits
  • Options for housing support
  • Visa sponsorship
  • 3% 401k matching
  • Health insurance

Apply