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Brain Machine Interface Jobs in California (NOW HIRING)

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

... brain-computer interfaces. This role sits at the intersection of ambitious research and rigorous ... Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end ...

Neuralink

CNC Machinist

South San Francisco, CA · On-site

$42.55 - $75.48/hr

The Machine Shop is a vital component of Neuralink's mission to develop the world's best and most manufacturable Brain-Computer Interface (BCI). Our team of skilled Machinists play a crucial role in ...

Brain Corp

Engineering Manager, Cloud

San Diego, CA · On-site

... intelligent machines. Position Summary: Brain Corp runs one of the world's largest fleets of ... interfaces * Define and execute the team roadmap aligned with company and Platform strategy ...

Brain Corp

Engineering Manager, Cloud

San Diego, CA · On-site

... intelligent machines. Position Summary: Brain Corp runs one of the world's largest fleets of ... interfaces * Define and execute the team roadmap aligned with company and Platform strategy ...

Brain Corp

Operations Lead, Walmart, Inc.

San Diego, CA · On-site

... machines. The Walmart Inc. Program Lead - Operations serves as the ultimate owner of the Brain Corp ... Primary Operational Interface : Serve as the primary point of contact for Operations for all ...

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 · 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, Next Gen

South San Francisco, 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 ...

Neuralink

Neuroengineer, Next Gen

South San Francisco, 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 ...

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 ...

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 ...

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How much do brain machine interface jobs pay per hour?

As of Aug 7, 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 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.

What is a brain machine interface?

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 August 2026, with employment types broken down into 74% Full Time, 20% Part Time, 2% Temporary, 2% Contract, and 2% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% 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

Re-posted 2 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.

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
  • Health insurance

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